AN ABSTRACT OF THE THESIS OF
RACHED AKROUT
for the degree of
MASTER OF SCIENCE
in Agricultural and Resource Economics presented on /0-otO "?&
Title:
ECONOMIC ANALYSIS OF THE LIMITATIONS TO THE
PRODUCTION OF BREAD WHEAT IN TUNISIA
Abstract approved:
//
Q
John A. Edwards
In order to effectively use wheat prices as tools of government
policy, it is necessary to investigate the possible effects of changes
in these prices on different economic variables.
In this study, at-
tempts have been made to estimate the effects of changes in wheat
prices upon:
1.
The allocation of the available wheat acreage between bread
wheat and durum wheat; and
2.
The use of fertilizer for further improvement of wheat yields.
In studying the farmer's acreage and yield response, respectively
special attention was given to economically controlled factors included
in the models, and estimates of the responses were developed for two
historical periods - 1949-1963 (the traditional period) and 1960-1974
(the modern period).
A detailed analysis of the behavior of economic
factors and a comparison of their magnitudes between the two major
periods of production are presented.
The results of the empirical study of farmer's acreage supply
response and yields response indicate that:
1.
Tunisian farmers are significantly responsive, in their
acreage allocation decisions, to relative output prices;
2.
Yields of the new high potential bread wheat varieties, recently introduced in Tunisia, are more responsive to
fertilizer use, under dry-land conditions, than the local
varieties; and
3.
The demand for fertilizer by Tunisian farmers is significantly
determined by farm-income and relative output prices.
This suggests that a policy which would raise the price of bread
wheat relative to that of durum wheat, other things the same, would
contribute to increasing overall bread wheat production and therefore
reducing governmental spending on bread wheat imports.
Economic Analysis of the Limitations to the
Production of Bread Wheat in Tunisia
by
Rached Akrout
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
June 1976
APPROVED:
Professor J/tmn A. Edwards
in charge of major
,.Y " '
Head of Department dlfl Agricultural and Resources Economics
Dean of Graduate Schoo'
Date thesis is presented
Typed by Susie Kozlik for
/0~&l&~7<^
Rached Akrout
ACKNOWLEDGMENTS
The author owes a special debt of gratitude to Dr. John A.
Edwards, major professor, for his ideas and valuable suggestions at
all stages of this study and guidance throughout the author's graduate
program at Oregon State University.
He would like to thank Drs. Bruce R. Rettig, Roger G. Petersen
and Timothy M. Hammonds, members of his graduate committee.
The author is under a deep obligation to his colleagues in the
Bureau du Plan et du Developpement Agricole, Tunis for collecting and
arranging the data which made this research possible and encouragement throughout the entire period of his graduate study.
Special thanks are also due to Drs. Malcolm J. Purvis and
Reynold P. Dahl -- the Department of Agricultural and Applied
Economics --at the University of Minnesota, for their help at the
initial stage of the study.
Indebtedness to my family for their encouragement throughout
this study, should be particularly mentioned.
TABLE OF CONTENTS
Chapter
I
Page
INTRODUCTION
Problem
Previous Related Researches
Objectives
II
METHODOLOGY
Hypotheses
Methodological Basis
The Acreage Supply Response
Yield Response
Estimation Procedures
Acreage Supply Response
Nerlove-Type Acreage Model
The Yield Model
III
IV
EMPIRICAL RESULTS
1
1
4
6
8
8
9
9
13
14
14
14
15
18
The Acreage Supply Response
The Traditional Production Period
The Modern Production Period
Yield Response
The Traditional Production Period
The Modern Production Period
The Demand for Fertilizer
The Traditional Production Period
The Modern Production Period
18
18
19
25
25
27
29
29
31
INTERPRETATION OF THE ESTIMATED RESULTS
33
The Acreage Supply Response
The Traditional Production Period
The Modern Production Period
The Yield Response
The Traditional Production Period
The Modern Production Period
The Demand for Fertilizer
The Traditional Production Period
The Modern Production Period
Comparison
33
33
37
40
40
42
42
42
43
44
Chapter
V
Page
POLICY IMPLICATIONS
The Acreage of Bread Wheat
The Yields of Bread Wheat
BIBLIOGRAPHY
45
46
51
60
APPENDIC ES
Appendix A: Basic Data
Appendix B: Estimation of Acreage and Yield
Responses for Durum Wheat
63
72
LIST OF TABLES
Table
1
2
Page
Tunisian domestic production and imports of bread
wheat during the period (1949-1974),
3
The estimated acreage supply response in the
traditional production period
20
The estimated acreage supply response in the
modern production period
23
The estimated yield response in the traditional
production period
£6
The estimated yields response in the modern
production period
28
The estimated demand for fertilizer in the
traditional production period
30
The estimated demand for fertilizer in the modern
production period
32
The'revised estimated acreage supply response in
the traditional production period
35
The revised estimated acreage supply response in
the.;modern production period
38
The acreage of wheat on Tunisian and European
farms during the period (1949-1958)
41
11
The average acreage of wheat in Tunisia (1949-19'74)
48
12
The Tunisian exports of Durum wheat (1957-1966)
49
13
The estimated per capita consumption of wheat bydegree of urbanization in Tunisia (1966) (in kilograms)
51
14
Projection of the production of cereals in Tunisia
52
15
Acreage adjustment to changes in relative prices (a)
5?''
16
Acreage adjustment to changes in relative prifces (b)
58
3
4
5
6
7
8
9
10
LIST OF APPENDIX TABLES
Table
1
Page
The acreage and yields of bread wheat and Durum
wheat in Tunisia (1949-1974)
64
The yields of bread wheat and the total annual rainfall
in Tunisia (1949-1974)
65
The wholesale prices of bread wheat, Durum wheat
and nitrogen in Tunisia (1949-1974)
66
The yields and prices of bread wheat relative to the
yield and price of Durum wheat and to the price of
fertilizer (1950-1974)
68
5
The estimated per capita income in Tunisia (1949-1974)
69
6
Annual yields and per hectare nitrogen use in bread
wheat production during the period (1949-1974)
70
The estimated Durum wheat acreage supply response
in the traditional production period
75
The estimated Durum wheat acreage supply response
in the modern production period
77
The estimated Durum wheat yield response in the
traditional production period
79
The estimated Durum wheat yield response in the
modern production period
81
2
3
4
7
8
9
10
LIST OF FIGURES
Figure
1
2
Page
Acreage of bread wheat and Durum wheat in Tunisia
(1949-1974)
47
Bread wheat acreage adjustment to relative price
changes
56
ECONOMIC ANALYSIS OF THE LIMITATIONS TO THE
PRODUCTION OF BREAD WHEAT IN TUNISIA
I.
INTRODUCTION
Problem
The production of wheat in Tunisia has been a dominant traditional agricultural activity for centuries.
It started with the Romans
who introduced the first seeds from different areas of their Empire
and continued through the recent French protectorate period during
which new techniques and processes of production were implemented
in the area.
In recent years, more than a third of the 3. 4 million
hectares of the cultivated land in the country have been devoted to wheat
production with 1/5 or less in bread wheat.
However, the major prob-
lem that characterized the production was, and still is, the presence
of a high variability in production levels from one harvesting year to
the other resulting in significant importation trends, specifically of
bread wheat, in the country.
As a matter of fact, the importation of
bread wheat in Tunisia was a recognized tradition since the introduction of this agricultural commodity by the French in the nineteenth
century, but in the last decade, it has taken a significant place among
the imported agricultural commodities in the country since bread wheat
imports accounted, on the average, for more than 70% of the total
imported agricultural commodities.
In an average year like 1962/1963
for example, the value of imported live animals, dairy products,
fruits and vegetables (which represent the major imported agricultural
commodities in Tunisia) was 8.2 million U. S. dollars, contrasted
with 19 million U. S. dollars of imported bread wheat.
On the other
hand, the percentage of imported bread wheat to the domestic total
production reached extremely high levels during the last 15 years.
In
fact, as is illustrated in Table 1, the average of imported bread wheat
as a percentage of the local production in the traditional production
period (1949-1963) was 118. 3, contrasted to an average of 256. 6 during
the modern production period (1960-1974).
This high importation trend of bread wheat is very suggestive,
in that, even with the recent transition from the past traditional production process to a relatively modern agriculture, the reliance of
the domestic demand on imported bread wheat is even higher.
In addition, with the recent emergence of a large tourist industry in the country (which counts for about one fourth of the domestic
population), and the high domestic population growth (3%), future bread
wheat production stimulations are inevitable and certainly needed to
meet the increasing domestic consumption trends.
The present research covers a very definite period (i. e. , 19491974) during which the production of bread wheat was characterized by
The information concerning bread wheat imports and values was
gathered from different issues of the United Nations trade yearbook.
Table 1.
Tunisian domestic production and imports of bread wheat
during the period (1949-1974).
Total Domestic
Production of
Bread Wheat
(1000. tons)
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
197^
1973
1974
Source:
180
180
120
230
200
190
100,
150
140
130
120
90
43
93
130
95
120
70
75
73
80
150
200
258
235
202
Total Tunisian
Imports of
Bread Wheat
(1000 tons)
14. 9
69. 4
4. 0
39.9
9.8
0;6
18.0
130. 1
118. 1
26.8
68.0
154. 1
366.5
271.8
157. 6
189.6
141. 3
249. 7
338. 7
211.6
381. 3
249. 1
16Y\0
212.0
291. 6
127.0
Tunisian Bread
Wheat Imports
. nn
r
^
x 100
Domestic
Prod[uction
8.0
38.5
3.0
17. 3
4.9
0.0
18.0
86.0
84.0
20.6
56.6
.171.2
853.0
292.2
121.2
199.5
117. 7
356.7
451. 6
289.8
476. 6
166.0
83.5
82. 1
124. 1
62.8
Ministere de I'agr icultur e, biireaudu plan et du development
agricole, enquetes statistiques.
two distinct stages:
1.
A first traditional production period which covers the range
(1949-1963), and during which the production of bread wheat
was highly extensive, and essentially reliant on economically
uncontrolled factors;
2.
And a modern production period covering the years (19631974) during which a new high yield technology was introduced in the production process essentially through the new
bread wheat varieties, and economically controlled factors
were sought for the improvement of domestic production
levels.
In addition, under each of these two major stages, the aggregate
bread wheat production in the country was characterized by:
A - A high variability of the annual average yields associated
with
B - A relatively significant variability of the acreage devoted by
the Tunisian wheat producers to bread wheat production from
one harvesting year to the other.
Previous Related Researches
In the available research studies related to this vital problem,
the work of MM John D. Hyslop, Reynold P. Dahl, and Malcolm J.
Purvis,
2
is acknowledged and highly contributive.
The former two
researchers, in an economic report submitted to the Tunisian Department of Agriculture in 1970 (10), tried to investigate some of the facts
that were, to an extent, at the origin of the wheat acreage variability
2
MM John D. Hyslop, Reynold P. Dahl and Malcolm J. Purvis
are Agricultural Economists, past members of the University of
Minnesota team in Tunisia.
in Tunisia on the basis of historical data covering the period 1950- "■I960.
Among their findings, the influence of world wheat prices as
well as climatic conditions in the area are worthwhile mentioning.
In
addition, in the same report, it was mentioned that the high variability
of domestic wheat yields during the decade 1950-1960 w ere dependent
upon the following three factors:
, :
1.
The rainfall in the area;
2.
The changes in the cultural practices by the Tunisian farmers;
3.
And some other political events.
Even though, the findings are most provocative, there was no attempt,
however, to quantify them for a further investigation of the problem.
On the other hand, M. Malcolm J. Purvis, in a recent article entitled
"The New Varieties Under Dry-land Conditions: Mexican Wheats in
Tunisia, " and published in the American Journal of Agricultural Economics (February 1973), tried to give some thoughts to the problems
facing the introduction of the Mexican varieties in Tunisia.
Specifi-
cally his main concern was to compare the yields of the local varieties
and those of the Mexican high yielding varieties under dry-land conditions.
And even though his findings are very well founded, there is
still some doubt about the degree of response of the local and the new
varieties to fertilizer, under similar dryland conditions.
Objectives
At the international level, an ever growing chorus of economists
and politicians warns of an impending, if not already existing, crisis
in world agricultural production and specifically in developing countries.
The President of the International Bank for Reconstruction and
Development, Georges D. Woods, has stressed the necessity for "much
greater emphasis on increasing production on the land both to feed
growing populations and to feed growing industries" (4).,
T. W.
Schultz, has addressed a book to this topic (20).
In Tunisia, particularly, a similar urgency for increasing the
production of bread wheat to meet the high domestic consumption has
been recognized; an increasing concern of the national agricultural
agencies as well as the Tunisian producers with the production of
bread wheat has developed and wide-range extension programs have
been undertaken as a result.
In contrast to this rapidly growing consensus about the existence
of critical problems in world agricultural production, and specifically
of bread wheat production in Tunisia, little agreement exists over
what policies might improve future prospects.
Jere B. Behrman (2)
is quoted to say
In the professional economic literature and in the policy discussions about underdeveloped agriculture, considerable
debate has raged over.the merits of various proposals.
Concurrence has not been possible, however, partly because
conflicting policy recommendations are implied by the
various .proposed "a priori" Hypothesis "about the supply
responsiveness of underdeveloped agriculture.
The present study is intended to give some insight into the response of the Tunisian bread wheat producers to economic factors in
their acreage allocation decisions, on one hand, and the response of
the yields to economic factors on the other.
Specifically, the study intends:
1.
to analyze the acreage supply response to economically
controlled and uncontrolled factors;
2.
to analyze yield response to economically controlled and
uncontrolled factors;
3.
and to give some thought to the possibilities and means of
increasing the domestic production of bread wheat under the
existing economically uncontrolled limitations.
II.
METHODOLOGY
Hypotheses
In the view of any economist, prices are important determinants
of economic behavior.
As a matter of fact, in his introductory eco-
nomic analysis (18), Paul A. Samuelson wrote:
At a higher price of wheat, farmers will take acreage out of
corn cultivation and put it into wheat, in addition, each can
now afford the cost of more fertilizer, more labor, more
machinery, and can even afford to grow extra wheat on
poorer land. All this tends to increase output at higher
prices.
However, it was argued by many western agricultural economists
(2) that in underdeveloped economies (Tunisia is one of them), the
response of farmers to changes in the prices of their output, in their
acreage allocation decisions, is irrational and uneconomical because
most of these countries are experiencing subsistence economies.
Also, it was argued, as mentioned earlier, that the new high yielding
varieties, introduced in Tunisia during the modern production period,
were developed under irrigated conditions, and their response to
fertilizer applications under dry land conditions such as the ones
existing in Tunisia, is inferior to the local varieties.
The main hypotheses to be tested here are:
1.
That the Tunisian farmers are responsive to the relative
prices of bread wheat to Durum wheat, among others, -*
^The other factors, however, will be explicitly discussed in the
following chapters of this study.
in their acreage allocation decisions;
2.
And the new wheat varieties introduced recently in the
Tunisian agriculture, are more responsive to fertilizer
applications (among others) than the local variety.
And, as a result of the second hypothesis, we shall be concerned also
with a secondary hypothesis; that the demand for fertilizer by the
Tunisian farmers is responsive to the farm income and the relative
prices of bread wheat to fertilizer.
Methodological Basis
The Acreage Supply Response
In the American economic literature at least, supply response
has been for more than two decades a central economic issue.
In fact,
one of the earliest attempts to apply this concept to production stimulation of certain American agriculture products was undertaken by W.
B. Hubbard in 1923 (7).
In 1925, B. Bradford Smith (22), noticed that besides the existence of an economic psychological relation between price and subsequent acreage, there is a need for a more intensive analysis in which
the selling price of the selected crop relative to the possible crops
should be considered, because this relative price is the chief factor
4
The other factors, however, will be explicitly discussed in a
later chapter.
10
influencing the net returns of the farmer.
In 1929, a leading agricul-
tural economist, J. D. Black (3), complained that many factors other
than the preceding year's relative price should be considered in any
investigation of acreage variations, such as damage from pests and
diseases, improvements in machinery for handling competing crops,
improvements in varieties or adaptability of competing crops.
The same year, in a study of farmer's response to price, L. H. /
Bean (1) noticed that the dominant factor in the change of acreage in a
given year for four different areas and nine commodities was the
preceding output price received by the farmers.
In addition, he pointed
out that factors such as the yields, weather, and profits have to be
taken into consideration because they may be assumed to influence the ,
farmer's actions,
Recently in a study of the supply dynamics of cer-
tain agricultural commodities in the United States, M. Marc Nerlove
advanced the theory that:
1.
the observed acreage devoted to an agricultural commodity —'
in any given year was linearily related to the acreage of the preceding
year adjusted to the difference between the expected long-run equilibrium acreage (i. e. , the acreage which would be reached if all the
necessary time taken by the farmers for price change adjustments _
was available) and the preceding year observed acreage;
2.
the expected price for the farmer's output in any given year
is linearily related to the preceding year expected price of output
1.1
adjusted to the difference between the preceding year observed and
expected prices.
By a simple process of substitution, he obtained a general linear
relationship between the actual acreage, the lagged observed price of
output and the lagged observed acreages (for one and two periods).
In other words, the Nerlovian supply dynamics system is expressed
as the following:
(1) X^X^ + YfX*-^)
><
*
(2) P^P^ + PfP^-P^)
(3)
X
t
=
%
+ a
l ^
where V and Pare the coefficients of adjustment and expectation respectively and such that:
o < Y < 1;
O<(3<1
X
is the desired long-run equilibrium acreage'.
P
is the expected price of output for a given harvesting year.
a, is a positive constant.
and t refers to time.
Substituting (3) and (2) into (1), we have:
X^X^ + v^+a^-X^)
X
t
= X
t-1
+
^o
+
*lt Pt-1
+ P (P
t-l " ^t-l^ "
YX
trl
12
X
Xt -
Yao + (l.v, X^j +
Xt=vao
+
+ pP
Xt
=
Yao
(
Ya1 (1-P)
(l-Y)Xt_1+va1
(l-P)
- a
^^
<Xt-l -
0)
X
+ PP,.!
t-2
+
^Xt-2 - Vao>
t-1
+
(1-Y)
Xt_1 +
(1^)(Y-1)
Xt_2 + (l-P) Xt_1 -
Y-
(l-P) + YajpP^j
Xt = Yao - Yao (l-P) +[ (l-P) + (1-Y)] X^ - (l-p)(l-Y) ^t_2
+ va
PP
Y
1 H t-1
Xt
= aoYp+ [(l-P) + (1-Y)] Xttl - (1-P)(1-Y) Xt_2 + yaj PP^j
And if we designate:
(4) ,o = ao YP
(5) uj = (l-P) + (1-Y)(>°)
(6) ^ =
(7)
-(1-Y)(1-P)(<O)
^3 = YajP (>o)
we can express the Nerlovian acreage supply model as the following:
X = if + / X
+u0X 0 + iT0P ,+u7
t
o
1 t-1
2 t-2
3 t-1
t
13
Yield Response
In a recent study covering the period 1944-1962 and concerning
the dependence of the yields of bread wheat in Tunisia on the annual
rainfall, an USAID Meteorologist, M. Lee Dutcher, found that during
dry years, the yields of bread wheat were concentrated below the period
average yield, and during the humid years, the yields were concentrated above it.
The correlation was^ significantly high.
In addition, he noticed that the correlation is even higher if the
rainfall between September and April
5
instead of the total annual
rainfall was taken into account.
On the other hand, in their economic report (Production de ble
en Tmnisie,
tendences et variabilites), MM. John D. Hyslop and
Reynold P. Dahl mentioned the impact of the changes in the rotation of
crops on the yields of wheat in Tunisia after the Second World "War.
M. Malcolm J. Purvis (16), in his discussion of the green revolution in the developing countries and in Tunisia particularly, noticed
that the new varieties of soft wheat are very responsive to fertilizer
application.
5
i
These results were taken from "Production de ble en Tunisie,
tendences et variabilites" by John D. Hyslop and Reynold P. Dahl,
May, 1970.
14
Estimation Procedures
Acreage Supply Response
Nerlove-Type Acreage Model
On the basis of the Nerlovian general supply dynamics theory,
the actual acreage devoted each year to bread wheat production by the
Tunisian farmers (X.) is hypothesized to be partly related to the lagged
observed relative prices of bread wheat to Duram wheat, and to the
lagged observed acreages for one and two periods, such that:
X
t
and tr
3
= Tr
o
+ 1T
l
X
t-1
+
^Xt-2
+
"Tz[^jt_1
+
utwhere V *2
are constants, —— is the relative price of bread wheat to
P
D
Durum wheat and u an error term which could partly be explained by
the relative lagged yields of bread wheat to Durum wheat and the total
annual rainfall, as it was pointed out earlier in the pioneering work of
MM, B. B. Smith, J. D. Black and L. H. Bean.
In other words, the
Tunisian farmers' acreage allocation decisions are hypothesized to be
partly influenced by output relative prices, relative yields, the preceding years acreage allocations, and the total annual rainfall in the
area.
Explicitly, the full acreage supply model would take the form:
15
+
where:
R
"5
t
+ U
t
X = the actual acreage of bread wheat
——I = the lagged relative prices of bread wheat to Durum
D/t-l
wheat
X
= one period lagged acreage of bread wheat
X
= two periods lagged acreage of bread wheat
,
D/t-l
the lagged relative yields of bread wheat to Durum
wheat
R = the actual total annual rainfall
U = random error term reflecting unidentified factors
a , a
... a
= average supply response parameters to be
estimated.
The Yield Model
On the basis of the research already mentioned, the yields of
bread wheat in Tunisia are hypothesized to be linearily related to fertilizer application, the total annual rainfall and the acreage devoted to
this agricultural commodity.
16
Explicitly, the statistical relation is:
6
Y = b + b (F ) + b'tR) + b. (A ) +i
t
o
It
2t
3t
t
where:
Y
= the average annual yield of bread wheat;
F
= the amounts of fertilizer applied per hectare;
R
= the total annual rainfall;
A
= the acreage of bread wheat;
I
= random error reflecting unidentified factors;
b ,b
o 1
, b0 = yield response parameters to be estimated.
3
In addition, an attempt is made in this study to estimate the
demand for fertilizer by Tunisian farmers as a response to changes
in the prices of their output.
Economic theory suggests that the quantity of a given fertilizer
demanded depends on the price of that fertilizer, the prices of related
commodities, and income (6).
This could be written as the following:
A more complete yield response model was developed here,
such that:
y
t
= K + (a
- a F )F + (6 - B R )R + yRF + e
oltt
oltt
ttt
or:
yt = K+«Ft+aFt+pRt+bRt +gV"t+et
where:
y, F, and R are bread wheat yields, fertilizer and rainfall
respectively;
K, a, a, (3, b and g are yield response parameters;
However, the estimated coefficients associated with the square and
cross-product terms were insignificant in the modern period.
17
F =C +C
t
o
1
^RV
*
P_
F
t
1
+ CM
+vY
2 t-1
t
where!
F
= the quantity of fertilizer demanded by Tunisian farmers
for bread wheat production;
(P )
= the lagged price of bread wheat;
B t- 1
F
F
= the actual price of fertlizer paid by Tunisian farmers;
t
M
"Y
= the lagged income of Tunisian farmers;
=
random error reflecting unidentified factors;
C , C , C_ = fertilizer demand parameters to be estimated,
o
i
2
18
III.
EMPIRICAL RESULTS
The Acreage Supply Response
The Traditional Production Period
The acreage response model was fitted to time series data
covering the period (1949-1963).
1.
The data used are:
The wholesale prices of bread wheat relative to that of Durum
wheat expressed in millimes
.7
per quintal, which are re-
ported by the appropriate service of the Tunisian Department of Agriculture at the end of each harvesting year;
2.
The total annual rainfall as the national total annual rainfall
in millimeters, which is reported by the world weather report at the 6nd of each year;
3.
The acreage of bread wheat harvested each year, in 1000
hectares, and reported either by the'Department of Agriculture or the Department of National Economy;
4.
The national annual average yields, computed as the ratio
of the total annual production to the acreage harvested in the
country.
They are reported by the appropriate service in
the Department of Agriculture in quintaux per hectare.
7
Millime is a Tunisian currency (1 dinar = 1000 millimes *s
2. 75 U. S. dollars).
19
The number of observations is 13.
Five regression equations
have been estimated using a stepwise statistical procedure. The
estimated acreage supply response functions are summarized in the
following table.
The estimated coefficient of the relative price of bread wheat
to Durum wheat is positive, highly significant in regression (1), and
significant at the 80% level in regressions (Z) and (3).
They have
relatively small standard errors and the R's squared associated with
the regressions (1) and (2) are statistically significant.
However,
the estimated coefficients of the total annual rainfall, the one period
lagged acreage, and the lagged relative yields, even though positive,
are not statistically significant, their standard errors relatively large,
and the R's squared associated with these variables are poor.
The
coefficient of the two periods lagged acreage is negative but statistically insignificant.
On the other hand, the absence of autocorrelation in the data
used is reflected in relatively high Durbin-Watson figures.
The Modern Production Period
The acreage supply response model was fitted to time series
data covering the period (1960-1974).
The data used included the same
items mentioned in the acreage response model fitted to the traditional
production period.
The number of observations is 13.
Five regression
Table 2.
The estimated acreage supply response in the traditional production period.
Variables
Regression
1
Parameter
S. E.
t
-465.19
280.290
-1. 6596
+756.37
330.556
2. 2818*
-322.11
+517.30
306.772
39 3.466
-1. 049
1. 315 . .
+ 28.415
25.952
-349.06
+541.64
331.477
419.583
x(2) = lagged relative
yields
+ 26.360
27.906
x(3) = total annual
rainfall
+
Constant
x(l) = lagged relative
prices
-318. 17
+492. 10
374. 452
489.800
-0. 849
1.,004
x(2) = lagged relative
yields
+ 24.66
30.491
0.,809
Constant
x(l) = lagged relative
prices /^BA
I PD/t-l
2
3
4
Coefficient
Constant
x(l) = lage;ed relative
prices / PB ]
I PD/t-1
x(2) = lagged relative
yields f^3-)
\YD/t-l
Constant
x(l) = lagged relative
prices
Durbin-Watson
R
2
i
0.0548
0.1532
1. 095
2.268
0.343
2.176
0.421
2.164
0.429
-1. 053
1. 2909 .
0. 944
0. 357
tv
o
Table 2.
Continued.
Variables
Regression
4 cont.
1.
Parameter
Coefficient
S. E.
t
x(3)=total annual
rainfall
+
0.0509
0.1638
0.3107
x(4) = lagged acreage
(one period)
+
0.0876
0.355
0.246
Constant
x(l) = lagged relative
prices
-306.62
+488.21
412. 118
528.91
-0.744
0.923
x(2) = lagged relative
yields
+23.746
33.527
0.708
x(3)=total annual
rainfall
+
0.0505
0.1767
0.286
x(4) = lagged acreage
(one period)
+
0.1238
0.4623
0.267
x(5) = lagged acreage
(two periods)
-
0.06948
0.495
0.140
Durbin-Watson
R
2
2.227
0.434
2.227
0.436
Notation: * Statistically significant at the 95% level.
. . Statistically significant at the 80% level.
Cs)
22
equations have been estimated, using a stepwise statistical procedure.
The estimated acreage supply response functions are summarized
in the table on the following page.
The estimated coefficients of the relative prices of bread wheat
to Durum wheat are positive, highly significant in each of the two first
regression equations, and relatively significant at the 80% level in the
remaining 3 regression equations fitted to the data.
Their standard
errors are quite small, and the R's squared associated with the lagged
relative prices are statistically significant.
The estimated coefficients of the relative yields of bread wheat
to Durum wheat and the one period lagged acreage are positive but, in
statistical terms, they are relatively insignificant.
Estimated coefficients of the two periods' lagged acreage are
positive and insignificant.
The coefficient of the total, annual rainfall is unexpectedly negative, insignificant (i.e. , in statistical terms); and its standard error
substantially large.
Finally, the absence of autocorrelation in the time-series data
used is reflected in relatively higher Durbin-.Watson figures.
Table 3.
The estimated acreage supply response in the modern production period.
Variables
Regression
1
Parameter
Coefficient
S. E.
t
Constant
x(l) = lagged
gged relative
relat
prices
-332.62
+619.05
247.359
289.067
-1.344
2.142*
Constant
x(l) = lagged relative
prices
-416.53
+756.36
285.22
364.27
-1.460
2.076*
Durbin-Watson
.
R
2
3.043
0.314
2.792
0.345
2.699
0.374
VPD/t-l
x(2) = lagged acreage
(one period)
0.177
0.2712
Constant
x(l) = lagged relative
prices
-377.36
+632.53
x(2) = lagged acreage
(one period)
+
0.1892
0.2819
0.671
x(3) = lagged acreage
(two periods)
+
0.1618
0.2660
0.608
Constant
x(l) = lagged relative
prices
-418.22
+707.90
x(2) = lagged acreage
(one period)
+
0.224
323.130
429.090
0.654
382.09
479.98
0.306
-1.044
1.474..
-1.094
1.474..
0.732
tv>
Table 3.
Continued.
Variables
Regression
4 cont.
5
Parameter
Coefficient
S. E.
x(3) = lagged acreage
(two periods)
+
0. 168
0.280
0.600
x(4) = lagged relative
yields
+ 16.815
36.159
0. 465
Constant
x(l) = lagged relative
prices
-520.81
+845.79
x(2) = lagged acreage
(one period)
+
0. 255
0.3262
0.783
x(3) = lagged acreage
(two periods)
+
0. 184
0.296
0.623
x(4) = lagged relative
yields
+ 28.38
x(5)=total annual
rainfall
1.
0. 113
438.15
556.77
42.84
0. 194
Durbin-Watson
R
2.691
0. 393
2.869
0.426
-1.188
1.519
0.662
-0.584
Notation: * Statistically significant at the 95% level.
. . Statistically significant at the 80% level.
to
25
Yield Response
The Traditional Production Period
The bread wheat yields response nnodel was fitted to time series
data covering the period (1949-1963).
1.
The data used are:
The amounts of fertilizer, conaputed as the ratio of the total
quantity of nitrogen units used by the Tunisian farmers each
year for bread wheat production to the total acreage harvested at the end of the year.
They are expressed in units
of nitrogen per hectare;
2.
The acreage of bread wheat as reported by the appropriate
Services in the Department of Agriculture, and expressed in
1000 hectares.
3.
The national total annual rainfall as reported by the world
weather report at the end of each year.
The number of observations is 15.
Three regression equations
have been estimated using a stepwise statistical procedure.
The es-
timated yields response equations are summarized in the table on the
following page.
The estimated coefficients of the total annual rainfall are positive, relatively significant (at the 80% level), but their standard
errors are quite large, and the associated R's squared low.
Table 4.
The estimated yield response in the traditional production period.
Variables
Regression
Parameter
1
Constant
x(l)=amounts of
nitrogen per
hectare
8.1327
-0.26568
0.7950977
0.2375050
10.22850
- 1.11862..
Constant
x(l)=amounts of
nitrogen
6.1784
-0.31684
2.1101919
0.242959
2.927881
- 1.304097..
x(2)=total annual
rainfall
+0.010660
0.0106623
0.999798
Constant
x(l)=amounts of
nitrogen
9.1185
-0.48295
6.35188979
0.4202559
1.435554..
- 1.1491758..
x(2)=total annual
rainfall
+0.012812
0.01184902
1.081230
x(3)=acreage of
bread wheat
-0.017214
0.03493137
-0.4928038
2
3
1.
Coefficient
S. E.
Notation: . . Relatively significant at the 80% level.
t
Durbin-Watson
R
2
0.087
1.385
0.157
1.480
0.176
27
On the other hand, the estimated coefficients of fertilizer are
relatively significant (at the 80% level), but negative and their standard
errors relatively large,, the associated R's squared quite low.
The
estimated coefficient of the acreage is negative, highly insignificant .
and with.a large standard error.
The explanatory power of the
acreage as an independent variable is poor.
Finally, the absence of
a high autocorrelation is reflected in a high Durbin-Watson statistic.
The Modern Production Period
The yield response model was fitted to time series data covering
the modern production period (1960-1974).
The data used included the
same items mentioned in the yields response model fitted to the traditional production period.
The number of observations is 15.
Three
regression equations have been estimated on a stepwise basis.
The
estimated yields response equations are summarized in the table on
the following page.
The estimated coefficients of fertilizer and total annual rainfall
are positive and highly significant in the 3 regression equations.
Their standard errors are small and, as independent variables, the
total annual rainfall and fertilizer have a highly significant explanatory
power in the model since more than 50% of the yield variation is explained by fertilizer applications only, and 70% by the two factors in
common.
Table 5.
The estimated yields response in the modern production period.
Variables
Regression
1
1.
Parameter
Coefficient
S. E.
Dur bin-Wat son
C onstant
x(l)=amounts of
nitrogen per
hectare
3.4796
+0.28640
0.940868
0.078726
3. 69833302
3. 6378775*=
Constant
x(l)=amounts of
nitrogen
0.38950
+0.20810
1.41808757
0.07196562
0.27466605
2.8916735**
x(2)=total annual
rainfall
+0.016182
0.00619610
2.612038**
Constant
x(l)=amounts of
nitrogen
-0.98619
+0.19963
1.9783517
0.07247994
-0. 4984909
2.7542746**
x(2)=total annual
rainfall
+0.014922
0.006323865
2.359590**
x(3)=acreage of
bread wheat
+0.0095770
0.0096011
0.9974898. .
1.486
0.504
1.387
0.684
1. 339
0. 710
Notation: ** Statistically, highly significant.
. . Statistically significant at the 80% level.
co
29
On the other hand, the estimated coefficient of the acreage is
positive, but relatively insignificant.
Its standard error is quite large
and the R squared associated with the acreage, as an independent
variable in the model, is poor.
The Demand for Fertilizer
The Traditional Production Period
The demand for fertilizer by Tunisian farmers was fitted to
time-series data covering the period (1953-1963).
1.
The data used are:
The wholesale prices of bread wheat and fertilizer as reported by the appropriate service in the Department of
Agriculture, expressed in millimes per quintal;
2.
The farm income measured by the per capita income of the
Tunisians as reported by The United Nations Statistical
Yearbooks. It is expressed in dinars (1000 millimes) per
year.
The number of observations is only 10, due to lacking data for the
period (1949-1952).
Two regression equations have been estimated
on a stepwise basis.
The regression equations are summarized in
the table on the following page.
The estimated coefficients of the relative price of bread wheat to
fertilizer are positive and significant in both regression equations at
Table 6.
The estimated demand for fertilizer in the traditional production period.
Variables
Regression
1
Parameter
S. E.
t
-15.863
9.600150
Relative prices
+16.053
7.9913200
Constant
-27.118
Relative prices
+16.132
8.6043411
1.8748852*
(PF)t
Lagged Income
+0.062044
0.14706532
0.42188019
rZBjt-1
28.609728
Durbin-Watson
-1.652381
Constant
fPB)t-l
2
Coefficient
2.0087801*
R
2
0.4021
1.720
-0.9478620
1.828
0.422
M
t-1
1.
Notation: * Statistically significant at the 95% level.
o
31
the 95% and 90% level respectively.
Their standard errors relatively
small and the explanatory power of the relative prices, as an independent variable, is statistically significant.
However, the estimated
coefficient of the lagged income is insignificant but positive;
Its
standard error relatively large and the R squared associated with
the lagged income low. The absence of autocorrelation is reflected in
a high Durbin-Watson statistic.
The Modern Production Period
The demand for fertilizer in the modern period was fitted to
time-series data covering the period (1960-1974).
The data used
included the same items to which the demand for fertilizer in the traditional period was fitted.
The number of observations is 15.
Two re-
gression equations have been estimated on a stepwise statistical
procedural basis.
These regression equations are summarized in the
table on the following page.
Table 7.
The estimated demand for fertilizer in the modern production period.
Variables
Regression
1
2
Parameter
Coefficient
S. E.
10.5155625
t
Constant
-27.388
Lagged Income
+0.17314
Constant
-35.228
Relative Prices
(PB)t-l
+4.0218
6.73741149
0.5969300
lagged Income
+0.18728
0.05483280
3.40929397**
Durbin-Watson
2
-2.604477
0.0483187465 3. 58328551**1
16.9959678
R
1.84
0.4969
2.747
0.5114
-2.072736
fPF)t
1.
Notation: ** Statistically, highly significant.
33
IV.
INTERPRETATION OF THE ESTIMATED RESULTS
The Acreage Supply Response
The Traditional Production Period
The initial hypothesis that Tunisian farmers respond to the relative prices of bread wheat to Durum wheat, in their acreage allocation
decisions, is supported by the empirical results.
Q
However, it is worthwhile to notice that, during this period, the
climatic conditions and essentially the rainfall were to a certain extent
of major importance in the eyes of the Tunisian farmers in their
acreage allocation decisions, as stated by MM. John D. Hyslop and
Reynold P. Dahl (10.).
In fact, most of the producers, if not all of
them, are usually influenced within certain limits, by the first rainy
days of the seeding season in November following the dry period of
summer.
But, due to high uncertainty about the weather forecasts
in the area and the very marked inter- and intra-seasonal variability
of the rainfall, the response of farmers to the rainfall was not reflected
in the regression analysis in which crop-year rainfall was approximated by total annual rainfall, even though the estimated coefficients
are still positive.
g
Statistically speaking, the lagged relative prices are the only
significant variable in the estimated regression equation.
34
On the other hand, the regression analysis reflected satisfactorily the fact that, after the Second World War, Tunisian farmers felt
the,need for more wheat production and there was a transition from
the traditional rotation idle land - wheat to the actual rotation of
bread wheat on bread wheat, as was stated by the two previously mentioned researchers.
However, it might partly be due to the relative
high.collinearity between the one and two periods lagged acreages
(r = O.SSl), that the response of the farmers to them was relatively
insignificant.
In fact, . eliminating the two periods lagged acreage
from the model and increasing the number of observations from 1 3 to
14*.-;as illustrated in the table below, the estimated coefficients of the
;One period lagged acreage were positive and essentially more indicative.
..Also,' it is'worthwhile, to.notice that, by dropping the two periods
lagged acreage, the farmers' response to the lagged relative price of
their output and the total annual rainfall was satisfactorily improved
in the model fitted to this'period.
In addition, the response of Tunisian farmers to the lagged relative yields, as reflected in the regression analysis, was relatively
insignificant partly due toithe considerations of the climatic conditions
by; most pf the farmers." during this period.
Table 8.
The revised estimated acreage supply response in the traditional production period.
Variables
Regression
1
2
Parameter
Constant
x(l)=lagged relative prices
\PD/t-l
Constant
x(l) = lagged relative prices
Coefficient
S. E.
t
-425.96
+712.66
242.0719
286.4632
-1.7596
2.4877**
-473.59
+748.60
255.5030
296.2350
-1.8535
2.5270**
Durbin-Watson
R
2
1.762
0.322
1.779
0.350
1.980
0.383
(•F§)t-1
3
x(2)=total annual
rainfall
+
0.086634
0.12078
Constant
x(l) = lagged relatiy.e .prict
tive
.prices
-390.50
+602.67
x(2)=total annual
rainfall
+
0.09599
0.12348
0.77734
x(3) = lagged
acreage of bread
wheat
+
0.21850
0.283838
0.769807
Constant
x(l) = lagged relative prices
-294.75
+457.60
281.4685
356.0536
-1.3873
1.69262.
(M
VPD/t-l
348.4856
468.6750
-0.84581
0.97637
Table 8.
Continued.
Variables
Regression
4 cont.
1.
Parameter
Coefficient
S. E.
t
x(2)=total annual
rainfall
+
0.08875
0.128729
0.689444
x(3) = lagged
acreage of bread
wheat
+
0.23328
0.29548
0.78946
x(4) = lagged relatlve yields
+ 12.661
25.2390
Notation: ** Statistically, highly significant.
Significant at the 90% level.
0.501628
Durbin-Watson
1.980
R
2
0.398
37
The Modern Production Period
The initial hypothesis that the Tunisian farmers are responsive
to the relative prices of bread wheat to Durum wheat is highly supported by the empirical, evidence during this period too.
But it should
be made clear that the absence of a significant difference between the
Tunisian farmers' response to the lagged relative prices in the traditional and the modern periods of production might partly be explained
by the relative high correlation between the two periods lagged
acreage and the lagged relative prices (r = 0.600).
9
Eliminating the
two periods lagged acreage from the model and increasing the number
of observations from 13 to 14 was undertaken in this study.
As a re-
sult, the estirnated coefficients of the lagged relative prices of bread
wheat to Durum, wheat appeared to be highly significant in the four
regression equations, their standard errors relatively small, and the
R's squared associated with the first two regression equations were
statistically significant, as illustrated in the following table.
In addition, as was mentioned earlier, due to the high instability
of the climatic conditions and the marked interT and intra-seasonal
•9 In Elements of Econometrics, Jan Kmenta mentioned that,
when there are more than 2 independent variables in the model, the low
magnitude of the correlation coefficients (r=0. 50 in :his example) are
sometimes underestimating the high collinearity between the pairs of
independent variables. For further information, see Jan Kmenta,
(13, p.. 482)'.'
Table 9.
The revised estimated acreage supply response in the modern production period.
Variables
Regression
1
2
3
4
Parameter
Constant
x(l) = lagged relative prices
Coefficient
S. E.
t
-475.08
+772.96
256.47549
300.54025
-1.8532
2.571899**
\PD/ t-1
Constant
x(l)=lagged relative prices
-593.09
+863.39
289.1093
318.5732
-2.0514
2.71019**
VPD/ t-1
x(2) = lagged relative yields
+30.300
lYD/t-l
Constant
-669.48
x(l)=lagged rela- +1001.8
tive prices
x(2)=lagged relative yields
+39.873
x(3)=total annual
rainfall
-
0.1024
Constant
-704.01
x(l)=lagged rela- _1009. 20
tive prices
33.3784
354.3211
412.3305
38.47958
0.1847327
394.49719
483.4049
0.90776
Durbin-Watson
_
R
2.178
0.337
2.106
0.379
2.085
0.396
-1.974138
2.42949**
1.036212
-0.554291
-1.784583
2.08759*
00
oo
Table 9.
Continued.
Variables
Regression
4 cont.
Parameter
Coefficient
S. E.
40.36315
Durbin-Watson
x(2) = lagged relative yields
+39.900
x(3)=total annual
rainfall
-
0.10218
0.1938430
-0.527113
x(4) = lagged
acreage of
bread wheat
+
0.010169
0.2970881
+0.0342285
1.
Notation: ** Highly significant.
. . Significant at the 95% level.
2.
Statistically speaking, regression (3) is significant.
R
0.988529
2.078
0. 396
00
40
variability of the rainfall in the country, the response of the Tunisian
farmers to the rainfall was insignificant and even negative in the regression analysis in which crop year rainfall was approximated by
total annual rainfall.
On the other hand, with the wide extension programs undertaken
by the Tunisian Department of Agriculture urging the farmers to grow
more new high yielding varieties of bread wheat, the positive response
to the lagged relative yields seems to be encouraging even though not
highly significant during the beginning of this period.
The Yield Response
The Traditional Production Period
The negative effects of nitrogen application and the acreage on
the yields, as reflected in the regression analysis, seem to be puzzling, but historical evidence shows that they are not.
In fact, during
this period, the average acreage devoted by the Tunisian farmers to
Durum wheat relative to bread wheat was more than 91%, as is illustrated in the table on the following page, and bread wheat was grown
on very marginal lands except on European farms.
In addition, it is worthwhile to notice here the poor contribution
of fertilizer to the explanation of the yields variability.
On the other
hand, even though the effect of rainfall was biased for the same reason
Table 10.
The acreage of wheat on Tunisian and European farms during the period (1949 - 1958).
Tunisian Farmers
Harvest
Year
Area in
Area in
Durum Wheat Bread Wheat
(1000 hectares)
European Farmers
Percent of
Total in
Durum Wheat
Area in
Area in
Durum Wheat Bread Wheat
(1000 hectares)
Percent of
Total in Durum
Wheat
1949
604
55
91.7
64
108
37.2
1950
443
53
89.3
85
115
42.5
1951
735
67
91.6
100
107
48.3
1952
830
78
91.4
122
126
50.8
1953
757
64
92.2
116
120
49.2
1954
1021
74
93.2
132
131
50.2
1955
690
65
91.4
144
123
53.9
1956
820
90
90.1
145
133
52.2
1957
958
83
92.0
135
119
53.1
1958
976
74
93.0
133
99
57.3
Source: Republic of Tunisia, Secretarial of State for plan and for the national economic and Annuaire
Statistique de la Tunisie, various issues.
t^.
42
mentioned earlier in this study, the positive sign of the estimated
coefficients reflects its impact on the yields, specifically during this
period.
The Modern Production Period
The response of the new high potential varieties to nitrogen
applications and rainfall is reflected by the time-series data fitted to
this period.
In fact, more than 50% of the yields variability are ex-
plained by nitrogen application and about 70% by the combination nitrogen - rainfall.
In addition, it is of interest to notice here, that the positive sign
of the estimated acreage coefficient reflects the recent tendency of
the Tunisian farmers to shift more of their potential lands to the new
varieties of bread wheat introduced in the country under3 the urgence of
the Tunisian Government.
The Demand for Fertilizer
The Traditional Production Period
The positive estimated coefficients of the relative prices of
bread wheat to fertilizer, in both regression equations, reflect a very
interesting result, in the sense that the Tunisian farmers were responsive in their purchases of fertilizer, to these relative prices.
43
In addition, the regression equations fitted to this period showed the
positive effect of income on the Tunisian farmers' purchases of fertilizer, even though the estimated coefficient was relatively insignificant.
The Modern Production Period
The hypothesis that there is a positive effect of farm-income
and price on the purchases of fertilizer by Tunisian farmers is supported by the empirical results related to this period, but, the
magnitude and the significance of the estimated coefficients related
to the two periods of production, in a certain way, seem to be misleading.
This might partly be due to the difference in the number of
observations fitted to each of these two periods.
In fact, the number
of observations used in the traditional period was only 10, compared
to 15 observations in the modern production period.
The reliability of the modern period estimates seems to be
plausible.
Furthermore, it is worthwhile to notice that, statistically speaking, the income-relative price effect is highly significant at the 95%
level, and with 12 degrees of freedom.
In fact, in the traditional period, the estimated coefficients of
the relative prices were statistically significant while in the modern
period they were not.
44
Comparison
A comparison of the empirical results underlying each of the tw<3
major periods of production in the country reveals that:
1. In the recent yearst the Tunisian farmers seem to be relatively more responsive, *■ in their acreage allocation decisions, to the relative prices (i. e. of bread wheat to Durum
wheat) than they were in the traditional period;
2. The response of yields to fertilizer applications in the modern
production period is substantially higher^ than their response
in the traditional period;
3. And, that in both periods, the demand for fertilizer was highly
related to farm income and the relative prices of bread wheat
to fertilizer.
l-'-The estimated coefficients of the relative prices related to the
two periods are not statistically different at the 95% level, but significant at the 80% level after the exclusion, of the two- periods lagged
acreage from the model.
l^The estimated coefficients of fertilizer, in the two periods,
are significantly different.
45
V.
POLICY IMPLICATIONS
The production of bread wheat in Tunisia has been a highly traditional agricultural activity for decades, although it was not as important as was the production of Durum wheat.
13
However, in the
last decade, with a flourishing domestic market and a high importation
trend, this agricultural commodity has attracted the attention of many
governmental agencies, researchers and producers as well.
As a
matter of fact, Tunisia was one of the first countries to try to change
the structure of the production pattern of this agricultural commodity
in the country by a progressive transition from a traditional agricultural sector, reliant to a high degree on economically uncontrolled
factors of production, to a modern sector under which some of the
major factors of production are controlled (16).
However, some of the practical limitations to the increase of
production in the country need more attention, essentially concerning
the Tunisian farmers' response to the prices of output in their acreage
allocation decisions, and the response of the new high yielding varieties
to fertilizer applications relative to the traditional local varieties
under similar climatic conditions.
l-^In fact, the average relative acreage of Durum wheat to bread
wheat was more than 91% for the period (1949-1958).
46
The empirical analyses covered by this study supports the hypotheses:
1.
that the Tunisian farmers are responsive to the relative
prices of bread wheat to Durum wheat, (among others),
in their acreage allocation decisions;
2.
that the new high yielding varieties, which were introduced
in the modern production period, are more responsive to
fertilizer applications, (among others), than the local
varieties and that the demand for fertilizer by the Tunisian
farmers is highly responsive to both farm-income and the
relative prices of bread wheat to fertilizer.
This implies a possibility that an appropriate price policy in
favor of bread wheat would contribute relatively more to achieving
increased domestic production with respect to an expected increase in
both the acreage and the yields.
The Acreage of Bread Wheat
The stagnation of bread wheat acreage at about 1/5 of
the acreage of Durum wheat for more than 25 years, as is illustrated
in the table and figure on the next two pages, could be true in the times
when Tunisia was among the major exporting countries of Durum
wheat in the world grain market, and the internal prices of bread
wheat were relatively low. (5).
1400 1300 1200
Durum
Wheat
1S1100 H
rtlOOO -\
-M
« 900 o 800
o
2 700
.2 600 -\
M
500 H
Z 400.. H
300
5
Bread
Wheat
200
100 -I
T
!—l
1
1
1—i
1
1
1
1
1
1
r
1949 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
Figure 1.
Year
Acreage of bread wheat and Durum wheat during the period (1949- 1974).
-j
48
Table 11.
The average acreage of wheat in Tuiiisia (1949-1974).
Average Acreage
1949-1969
Average Acreage
1959-1969
Average Acreage
1960-1974
(1000 ha)
Durum Wheat
874
8 48
855
Bread Wheat
170
154
176
1044
1002
1031
Total
Ratio:
Durum Wheat
Bread Wheat
The Average Ratio:
Source:
5. 14:1
5.51:1
4.86:1
5. 17:1
Production de ble en Tunis ie, tendences et variabilites.
However, with the'recent:
1.
vanishing privileges of Tunisian Durum wheat in the French
market as well as in the world market;
2.
higher internal prices of bread wheat;
3.
and, the higher population growth
the Tunisian exports of Durum wheat disappeared, as-it is illustrated
below, and the need for a revision of the-internal pricing piOlicy in
favor of bread wheat seems to: be in. actual evidence.
Even though the domestic demand for Durum wheat is highly
inelastic, 14 the possibility of directly stimulating Tunisian farmers to
allocate more of their lands to bread wheat production by the means
M. John D. Hyslop found an average pif ice elasticity of (-0. 2)
in a projection analysis of wheat consumption in Tunisia.
49
Table 12.
The Tunisian exports of Durum wheat 1957-1966.
(1000 tons)
1957/58
1958/59
1959/60
1960/61
1961/62
1962/63
1963/64
1964/65
1965/66
1966/67
1967/68
1968/69
,
129
154
150
87
17
47
132
17
103
1
1
0
of higher relative prices (i. e. of bread wheat to Durum wheat), other
things being equal, could be highly practical, in recent years, for two
main reasons:
1.
The recent introduction of high yielding varieties of Durum
wheat in the country;
2.
And the expected higher income levels of Tunisian consumers.
In fact, during the modern production period, high yielding
Canadian and American varieties of Durum wheat were successfully
developed, 1 5 and as it was reported in a recent statistical survey (25),
the yields of the new varieties are significantly superior to the local
varieties under similar growth conditions.
1 See also my own empirical results developed in Appendix B of
this study.
50
Consequently, with an increasing care of the Tunisian farmers
about:
1.
the.application of sufficient amounts of fertilizer in Durum
wheat production;
2.
the w^eed
control which 'is a major problem in the intensive
areas of production;
3.
and, the application of a proper crop rotation
the switch of an expected higher acreage from Durum wheat to bread
wheat would probably be compensated by expected higher yields of
Durum wheat.
On the other hand, -the-expected price increase would probably
be reflected in a higher farm-income le.vel which inneans a higher consumer income (since more than 60% of the Tunisian population are engaged in agriculture), and more bread wheat production; since in a
recent statistical survey, M. John D. Hyslop found that the consumption of bread wheat versus Durum wheat, was highly related to the
income level of the consumers.
In fact, as it is illustrated in the
table below, the consumption of bread wheat in the large cities (higher
income levels) was reported to be significantly higher than in the
small counties (lower inco>me levels).
51
Table 13.
The estimated per capita consumption of wheat by degree
of urbanization in Tunisia (1966) (in kilograms).
Cereals
Large cities
Counties
Others
Total
Durum wheat
50.0
88.1
99.0
85.2
Bread wheat
80.0
70.1
60.0
66.7
Source: Une analyse de quelques politiques possibles de ble en
Tunisie. Report of a research in Agricultural Economics #3,
by John D. Hyslop, University of Minnesota.
In addition, a recent analysis of the demand for wheat in Tunisia
undertaken by the same economist cited above aiujl who was working on
the projection of wheat production in Tunisia (12), showed that, beyond
a certain level of income (estimated at about 200 U. S. dollars per
capita);
1.
the per capita consumption of durum wheat was inversely
related to the individual income level;
2.
and the per capita consumption of-btread wheat positively related to the income level, as it is■ illustrated in the projection table on the next page.
This implies that any relative "price increase would certainly
require more attention to a further increase of bread wheat acreage
in the country.
The Yields of Bread Wheat
The possibility of a revision of the pricing policy in favor of
52
Table 14.
Projection of the production of cereals in Tunisia.
Per Capita Consumption of Wheat
(kgs.)
Durum wheat
(kgs • )
1966
66.7
85. 1
1968
69.9
84. 7
1970
73. 1
84. 0
1972
76.1
83. 2
1974
79. 1
82. 0
1976. ,
81. 7
80. 7
1978
84. 5
79. 3
1980
8-7.0
77. 5
1982
89.3
75. 6
: 1984
91. 4
73. 5
1986
93. 4
71. 2
Period
Bread wheat
Source: Une analyse de quelques politiques de b'le possibles en
Tunisie. Report of a research in Agricultural Economics #3,
by John D: Hyslop, University of Minnesota.
bread wheat, other things being equal) on the other hand, is expected
to have a positive impact on the domestic yields with respect to:
1.
The expected stimulus to fertilizer applltatibn by the
Tunisian farmers;
2.
And, the increase of their individual incorrie levels.
In fact, on the basis of the empirical results "covered by this
study, the demand for fertilizer by the Tun'isiaii farme'rs was revealed
to be positively responsive to the relative prices of bread wheat (to
fertilizer), and the new varieties, recently introduced in the country,
53
highly responsive to fertilizer applications.
This implies that an
appropriate pricing stimulus would be reflected in a substantial improvement of yields.
This indi'rect positive impact on yields is highly
suggestive and should not be overlooked insofar if the main objective
is to achieve an increasing domestic production.
On the basis of the empirical results discussed in Chapter II of
this study, the demand for fertilizer by Tunisian farmers was revealed
to be highly determined by farm-income.
In fact, about 50% of the
variation in the quantities demanded by farmers were explained by.
variations in their income.
This implies that, in-a developing nation
like Tunisia with a relatively high rural population (60% of the total
population), any expected revision of the internal pricing, policy in
favor of this basic agricultural commodity (i. e. bread wheat) would
eviden.tly improve farm-income, thereby increasing the use of fertilizer, and consequently, other things being equal, the dbmestic yields
would substantially improv;e due to the high response of the new varieties successfully developed in the area.
It should be made clear at this stage, that aTnScessary time of
adjustment to any appropriate price revision should1 be expected, and
achieving an equilibrium domestic production level is a long-run
•adjustment procedure.
On this matter, a leading' American agricul-
tural economist, John D. Black can be quoted (3):
54
. . . the full effects of a definite change in relative prices for
a given product will take several years to appear. The fact
of the time of the response is fully as important as the
amount of it. If the change in prices is merely temporary,
lasting for two years, let us say, the response will be
headed off before it has happened.
In fact, the empirical results developed in this study can be helpful
in determining the length of time required to make full adjustment to
a change in relative wheat prices.
During the modern production
period, other things being the same, the actual acreage devoted each
year by Tunisian farmers to bread wheat production is determined by
the lagged relative price of bread wheat to that of Durum wheat and
the one period lagged acreage such that:
Numerically expressed as:
(1)
where the coefficient of price expectation, p, is equal to 0.8Z3
(P = 1 - 0. 177).
Assuming that, initially (t = 0), Tunisian farmers
/PB\
have reached a long-run equilibrium at a relative price j ——I of 0.82
\ D/
which has been held constant for a sufficiently long time, we could
write:
This is the simplified form of the original general Nerlovian
Model after the elimination of the two-periods lagged acreage (i. e. ,
the coefficient of adjustment, -y, is equal to one), because this latter did
not make a significant contribution in the model.
55
the acreage equilibrium would then be such that:
(2)
or:
x
= 247. 49 .
Suppose now that after a certain price revision in favor of bread wheat
a new relative price of 0.89 was set once and for all so as to stimulate
domestic bread wheat production; in period t = 1, the Nerlovian expected price of bread wheat to that of Durum wheat would be such that:
B 1*
B
*
D/l
D/ o
(P
+ P
B
\p«)
D/ o
\\pJ
D/
o
or:
B I*
0.82 + 0.823 (0.89 - 0.82) = 0.878
D /I
Replacing f—— I and x
D
x
by their respective values in (1), we have:
= 416.5 3 + 0. 177 (247. 49) + 756. 36 (0.8 78)
or:
x1 = 291.065
Similarily, in period t = 2, the expected relative price of bread wheat
to that of Durum wheat would be:
_B
D/l
or:
J3 I*
+ P
D/ 1
D/I
X
Path of adjustment before the price decrease
CO
(0
U
nl
310
-tj
o
<u
X!
o
o
o
n)
a)
300
-
290
-
Path of adjustment after the price decrease
280
270
nl
ID
!H
260
-
250
-
^3
0)
bJO
ni
0)
240
o
<
~
2 30
r
220
210
>
1_
0
Figure 2.
T-
3
4
7
Bread wheat acreage adjustment to relative price changes.
Ul
5?
'
=0.878 +0.823 (0.89 - 0.8 78) =0.888
Replacing! ——I and x
x
in (1), we get:
= -416. 63 + 0. 177 {291. 065) + 756. 36 (0. 888)
or:
x
= 306. 49
This average adjustment estimation has been carried out for five
periods as illustrated in the table below and Figurte 2.
From (2), the
hew equilibrium would be:
xV = -416. 53 + 0. 177 x* + 756. 36 (0. 89)
or:
x* = 311.82
Table 15.
Acreage adjustment to changes in relative prices (a).
Period (t)
Relative[_B]
Price
l^n/t
^
' "
Expected / B\ *
Relative I'P*'^. I.
Price
^
'
Acreage
(x )
% of
adjustment
0
1
2
3
4
0.82
0.89
0.89
0.89
0.89
0.8200
0.8780
0.8880
0.8896 '
0.8899
247.490
291.065
306.490
310.570
311.520
67.74
91.71
98.06
99.53
n
0.89
0.8900
311.820
100.00
58
This indicates that an increase of 7% in the relative price of bread
wheat could lead to a 26% increase in acreage in the long run.
It is
significant, however, to note that 67. 74% of the adjustment to the new
long run equilibrium would be accomplished in the first year following
the change in relative price and 99. 53% within the first four years.
However, the effects of this price increase could be aborted before
its full effect has been attained.
In fact, suppose that in period t = 2,
/PB\
the relative price \——I temporarily falls to 0. 85, due to, say, a high
\ D/
domestic supply of bread wheat. An expected lower equilibrium level
will be sought by farmers and the path of adjustment will tend to deviate from its initial course depending upon the magnitude of price
change as is illustrated in the table below.
Table 16.
Period (t)
Acreage adjustment to changes in relative prices (b).
Relative/ Bj
PriCe
P
i D/t-l
Expected/
Relative I
Price
^
B )*
Mt
Acreage
(xt)
0
1
2
3
0.820
0.890
0.850
0.890
0.820
0.878
0.855
0.884
247. 49
291.06
281. 67
301. 94
n
0.890
0.890
311.82
However, there is a possiblity .of accelerating the attainment of
such an equilibrium, and this is by improving the training programs
of the Tunisian agricultural extension agents and providing them with a
59
relatively large scope of action throughout the country so as to create
an effective propaganda which was described by John D. Black as an
important factor for the success of any governmental production program when he wrote-(3):
... it is surely true that as time goes on, and this (propaganda) and related problems are better understood, and
farmers learn from experience that production programs
recommended to them by responsible extension agencies
are well founded, acreages will be greatly influenced by
such means.
Finally, it should be stressed that this study was not supposed
to cover the whole problem and additional work on this subject is
recommended by the author.
60
BIBLIOGRAPHY
1.
Bean, Louis H. , "The Farmers Response to Price. " Journal
of Farm Economics, vol. II (1929), pp. 368-85.
2.
Behrman, J. R. , Supply Response in Underdeveloped Agriculture, Amsterdam, 1968, p. 1-18 and p. 151-170.
3.
Black, J. D. , Elasticity of Supply of Farm Products, Journal
of Farm Economics, April, 1924, vol. VI, p. 145-155.
4.
Closer Farm-Factory Tie Urged on Poorer Lands by World
Bank, New York Times (New York), p. 5, February 26, 1966.
5.
Dahl, R. P. , International Trade and Price Prospects for
Cereals and Their Implications to Tunisia, Marketing Report
no. 5, January, 1970.
6.
Ferguson, C. E. , Microecononaic Theory, Third Edition,
Richard D. Irwin, Inc. , 1972.
7.
Hubbard, W. B. , Cotton and the Cotton Market, D. Appleton &
Co. , 1923, p. 20.
8.
Hyslop, J. D. , Analyse de politiques possibles de production
Cerealiere en Tunisie, Rapport de Recherche en Economie
Agricole no 3, Juin, 1971.
9.
Hyslop, J. D. and Dahl, R. P. , Prix du ble et Politique de Prix
en Tunisie, Rapport de Recherche en economie agricole no 2,
Avril, 1970.
10.
Hyslop, J. D. and Dahl, R. P. , Production de ble en Tunisie:
Tendences et variabilities, Rapport de recherche en economie
agricole no 1, Mai; 1970.
11.
Hyslop, J. D. and Dahl, R. P. , Wheat Prices and Price Policy
in Tunisia, Staff paper, University of Minnesota, June, 1970.
12.
Hyslop, John D. , The Tunisian Cereals Sector: An Exannination
of Production, Prices, and Some Alternatives for the Future,
Institute of Agriculture, University of Minnesota, June, 1970.
■'61
13.
Kmenta, Jan, Elements of Econometrics - New York, 1971.
14.
Nerlove, Marc, The Dynamics of Supply: Estimation of Farmers'
Response to Price, Baltimore, 1958.
15.
Owen Tvirak, Factors Determining the Price of White Wheat in
the Pacific Northwest, Washington State' lifrilversity, November
18, 1974.
16.
Purvis, M. J. , "The New Varieties Under Dry-land Conditions:
Mexican Wheats in Tunisia," Ameriiian Journal of Agricultural
Economics, vol. 55, no 1, February, 1973.
17.
Republic of Tunisia, le journal officiel de la Republique Tunisienne-Lois et Reglements - Prix des cereales - June, 1974.
18.
Samuelsbn, Paul A. , Economics, An'Iritrbductory Analysis,
Sixth edition. New York, 1964.
19.
Schultz, T. W. , Economic Crises in World Agriculture, the
University of Michigan p^'ess. September, 1964.
20.
Schultz, T. W. , Food for'the World.
Press, 1945.
21.
Schultz, T. W. , Production and Welfare of Agriculture, New
York, the MacMillan Company, 1949.
22.
Smith, B. B. , "Forecasting the Acreage of Cotton, " Journal of
American Statistical Association, 1925, vol. 20, p. 31-47.
23.
Snedecor, George W. and Cochran, William G. , Statistical
Methods - Sixth Edition, Iowa State University, 1937.
24.
Tunisian Ministry of Agriculture - Budget Economique 1973, la
production.
25.
- Bureau du Plan et du developpement agricole
(B. P. D. A. ), enquetes statistiques, 1974.
26.
_^
- Comptes ressources-emplois des produits de
1'agriculture et de la Peche (1964-1968).
University of Chicago
62
27.
Tunisian Ministry of Agriculture
(1970-1972).
28.
- Prix moyens des produits de 1'agriculture
et de la Peche (1965-1972).
APPENDICES
63
APPENDIX A: BASIC DATA
64
Appendix Table 1.
Period
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
The acreage and yields of bread wheat and Durum
wheat in Tunisia (1949-1974).
Acreage of
Bread Wheat
(1000 hectares)
Acreage of
Durum Wheat
(1000 hectares)
170
170
170
200
180
200
180
220
210
180
180
190
110
100
170
180
180
160
180
180
145
280
200
260
230
195
675
520
830
975
875
1175
825
1100
1100
1150
1150
800
700
930
900
890
675
675
600
700
600
750
700
1000
1020
1046
/
Bread Wheat
(qx/ha)
11.0
10.8
7. 1
10.8
11.0
9.3
5.5
6.3
6.0
5,2
5.0
4.0
3.8
6.8
8.0
4.7
5.5
3.0
2.5
5.5
5.5
5.4
10.0
9.9
10.2
10.4
Durum Wheat
(qx/ha)
5.5
5.4
2.5
5.0
4.5
3.8
3.5
3.4
3.3
3.7
3.6
3.3
2.2
4.0
5.3
3.5
4.0
3.8
3.8
4.0
3.8
4.9
5. 7
7.5
6.7
6.6
/
Source: Production de BLE EN TUNISIE, Tendences et Variabilites
65
Appendix Table 2.
Period
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
Source:
The yields of bread wheat and the total annual
rainfall in Tunisia (1949-1974).
Total Annual Rainfall
(Millimeters/year)
150
150
155
303
233
136
66
139
232
250
256
191
170
195
265
250
320
94
150
270
300
172
200
314
350
350
Yields of Bread Wheat
(quintaux/hectare)
11.0
10.8
7. 1
10.8
11.0
9.3
5.5
6.3
6.0
5.2
5.0
4.0
3.8
6.8
8.0
4. 7
5.5
3.0
2.5
5.5
5.5
5. 4
10.0
9.9
10.2
10. 4
World Weather Records and Monthly Climate data for the
world.
Appendix Table 3.
Period
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
The wholesale prices of bread wheat. Durum wheat and nitrogen in Tunisia
(1949-1974).
Wholesale Prices of
Bread Wheat
(Mil limes /quintal)
2500
2600
3600
3600
3600
3400
3400
3450
3450
3596
3450
3450
3450
3450
3450
3450
3450
3450
4300
4300
4300
4300
4300
Wholesale Prices of
Durum Wheat
(Millimes/quintai)
2932
3172
4140
4140
4140
3910
3910
3967
3967
4468
4200
4200
4200
4200
4200
4200
4200
4200
4800
48 00
48 00
4800
4800
Wholesale Prices of
Nitrogen
(Millimes/quintai)
3140
3160
3160
3240
2493
2677
2677
2677
28 30
3616
3616
3100
4600
3000
3000
3000
Appendix Table 3.
Period
1972
1973
1974
Continued.
Wholesale Prices of
Bread Wheat
(Millimes /quintal)
4300
4300
5300
Wholesale Prices of
Durum Wheat
(Millimes /quintal)
4800
4800
5800
Wholesale Prices of
Nitrogen
(Millimes/quintal)
3000
5000
5000
Not officially reported
Source: Republic of Tunisia, Secretarial of State for plan and for the national economic and
Annuaire Statistiques de la Tunisia, various issues.
68
Appendix Table 4.
The yields and prices of bread wheat relative to
the yield and price of Durum wheat and to the price
of fertilizer (1950-1974).
Period The Relative Yields
lTD/t-1
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
Note:
2.00
2.00
2.85
2.27
2.58
2.58
1. 72
2.04
2.12
2. 12
1.78
1.33
1.75
1.72
1.51
1.35
1.23
0.91
0.71
0.91
1.11
1. 11
1.75
1.54
1.54
The
elative Prices
Dlt-l
0.85
0.82
0,87
0.87
0.87
0.87
0.87
0.87
0.87
0.80
0.82
0.82
0.82
0.82
0.82
0.82
0.82
0.82
0.89
0.89
0.89
0.89
0.89
0.89
0.89
The table is derived from previous data.
The Relative Prices
fPB) t-1
(PF) t
-
1.08
1.09
1.09
1.11
1.38
1.29
1.29
1.29
1.22
0.95
0.95
1.11
0.93
1.43
1.43
1.43
1.43
0.86
0.86
69
Appendix Table 5.
Period
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
The estimated per capita income in Tunisia
(1949-1974).
Estimated Total
Population (1000)
3416
3470
3500
3560
3630
3680
3745
3780
3815
3852
4105
4168
4254
4290
4304
4355
4675
4787
5067
5194
5300
5432
5568
Estimated Gross
National Product
(Million dinars)*
240
246
233
249
238
270
258
283
315
320
337
358
406
399
409
444
441
48 4
544
Per Capita
Income
(U.S. Dollars)
181
183
171
181
171
192
173
187
203
205
215
226
239
229
222
235
229
245
269
-
Source: United Nations - Statistical Yearbook - different issues.
*1 Dinar = Tunisian currency = 2. 75 U. S. dollars.
- Not officially reported.
Appendix Table 6.
Annual yields and per hectare nitrogen use in bread wheat production during the
period (1949-1974).
Period
Production of
Bread Wheat
(1000 T)
Yields
(qx/ha)
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
180
180
120
230
200
190
100
150
140
130
120
90
43
93
130
95
120
70
75
73
80
150
11. 0
10.8
7. 1
10.8
11.0
9.3
5.5
6.
6.
7.
6.
4.0
3.8
6.8
8.0
4. 7
5. 5
3.0
2.5
5.5
5.5
5.4
Quantity of Nitrogen
Used in Bread Wheat
Production IT/U-F. )
100
78
113
153
103
91
76
94
84
73
480
369
531
947
1097
1281
1385
915
1591
899
1680
2717
Acreage of Bread
Wheat (1000 ha. )
170
170
170
200
180
200
180
220
210
180
180
190
110
100
170
180
180
160
180
180
145
280
Quantity of
Nitrogen
(U. F. /ha)
0.588
0. 458
0.664
0.765
0.572
0.455
0.422
0.427
0.400
0.405
2.666
1.942
4.827
9.470
6.453
7. 116
7.694
5. 178
8.8 38
4.994
11.586
9. 703
o
Appendix Table 6.
Continued.
Period
Production of
Bread Wheat
(1000 T)
1971
1972
1973
1974
200
258
235
202
Yields
(qx/ha)
10.0
9.9
10. 2
10. 4
Quantity of Nitrogen
Used in Bread Wheat
Production (T/U- F. )
4400
2072
3538
5280
Acreage of Br ead
Wheat (1000 h;a.)
200
260
230
195
Quantity of
Nitrogen
(U. F. /ha)
22.000
7.969
15.382
27.076
Source: Production de BLE EN TUNISIE, Tendences et Variabilites and FAO, production
yearbook, various issues.
72
APPENDIX B: ESTIMATION OF ACREAGE AND
YIELD RESPONSES FOR DURUM WHEAT
EMPIRICAL RESULTS AND COMMENTS
73
Durum "Wheat Acreage Supply Response
The Traditional Production Period
The Nerlovian-type acreage response model discussed earlier
18
(i. e. , in Chapter II of this study) was fitted to time series data covering the period (1949-1963).
1.
The data used are:
The wholesale price of bread wheat relative to that of Durum
wheat expressed in millimes per quintal, which are reported
by the appropriate service of the Tunisian Department of
Agriculture at the end of each harvesting year;
2.
The total annual rainfall as the national total annual rainfall
in millimeters, which is reported by the world weather report at the end of each year;
3.
The acreage of Durum wheat harvested each year in 1000
hectares, and reported either by the Department of Agriculture or the Department of National Economy;
4.
The national annual average yields computed as the ratio of
the total annual production to the acreage harvested in the
country.
They are reported by the appropriate service in
the Department of Agriculture in quintaux per hectare.
l°The model indicated here, is the simplified form of the Nerlovian general model obtained after the elimination of the two-periods
lagged acreage which was highly correlated with the one period lagged
acreage.
74
The number of observations is 15.
Four regression equations have
been estimated using a stepwise statistical procedure.
The estimated
acreage supply response functions are summarized in the following
table.
The estimated coefficients of the lagged acreage and rainfall are
positive and significant, their standard errors quite small, and the
explanatory power associated with these two variables is significant.
However, the estimated coefficients of the lagged price of bread wheat
relative to that of Durum wheat are positive and insignificant, indicating the indifference of Tunisian farmers, in their acreage.alloca19
tion decisions, to changes in relative prices of their output.
The
absence of autocorrelation in the data used is reflected in a higher
Durbin-Watson Statistic.
The Modern Production Period
The acreage supply response model was fitted to time series data
covering the period (1960-1974).
The data used included the same
items mentioned in the acreage response model fitted to the traditional
production period.
The number of observations is 15.
Four regression equations
have been estimated using a stepwise statistical procedure.
19 In part, this result stresses the period of "production for subsistence" which arose in the country after the Second World War.
Appendix Table 7.
Variables
Regression
The estimated Durum wheat acreage supply response in the traditional production
period.
^_^
Parameter
Coefficient
S.E.
Durbin-Watson
R<
C onstant
Lagged Acreage
of Durum Wheat
Constant
Lagged Acreage
of Durum Wheat
Total Annual
Rainfall
C on s tant
Lagged Acreage
of Durum Wheat
Total Annual
Rainfall
Relative Lagged
Prices /PB |
550.91
+ 0.41998
224.859769
0.24124
2.4500
1.74085.
360.57
+ 0.41814
256.4816
0.232471
1.4058
1.3869..
0.98073
0.707127
1.7986..
- 27.361
+ 0.41720
1537.51
0.243049
+
+
1.0074
0.74651
+453.54
1769.99
-196.01
1964.150
0.281428
0.789048
3.03
0.2016
2.03
0. 3204
2. 18
0.3248
-0.01779
1.71654. .
1.34947. .
0.25623 NS
\^l t-1
Constant
Lagged Acreage
Total Annual
Rainfall
Relative Lagged
Prices
Relative Lagged
Yields /YB ^
Notation:
+
0.39944
+
1.0181
+723.61
- 24.044
VYD/t-l
Significant at the 80% level
-0.09979
1.41933..
1.29027. .
2578.136
0.28067 NS
158.624
-0. 15157 NS
NS Not significant
0.3266
~4
76
The estimated acreage supply response functions are summarized in the table on the following page.
The estimated coefficients of the lagged acreage and rainfall are
positive and significant, their standard errors small, and the explanatory power of these two independent variables is significant.
The
estimated coefficient of the lagged relative prices (even though statistically insignificant) is negative indicating the recent tendency of
Tunisian farmers to allocate less of their wheat acreage to Durum
wheat when the relative price of this commodity is expected to be low.
The high Durbin-Watson statistic indicates the absence of autocorrelation in the data used.
Durum Wheat Yield Response
The Traditional Production Period
Durum wheat yield response model
data covering the period (1949-1963).
1.
20
was fitted to time series
The data used are:
The amounts of fertilizer, computed as the ratio of the total
quantity of nitrogen units used by the Tunisian farmers each
year for Durum wheat production to the total acreage harvested at the end of the year.
They are expressed in units
of nitrogen per hectare;
20
This model was discussed earlier in Chapter II of this study.
Appendix Table 8.
Variables
Regression
The estimated Durum wheat acreage supply response in the modern production
period.
^_
Coefficient
Parameter
S.E.
Durbin-Watson
R'
Constant
Lagged Acreage
of Durum Wheat
Constant
Lagged Acreage
of Durum Wheat
Total Annual
Rainfall
Constant
Lagged Acreage
Total Annual
Rainfall
Relative Lagged
Yields
Constant
Lagged Acreage
Total Annual
Rainfall
Relative Lagged
Yields
Relative Lagged
Prices
1
402.14
+ 0.51594
182.876
0.21022
2.1989
2.4542*
180.51
+ 0.51875
190.736
0.18533
0.94638
2.79904*
0.42117
2.17438.
205.281
0. 188109
0.43144
0.53659
2.6179*
1.93365.
+
0.91579
110.15
+ 0.49246
+ 0.8 3426
+ 77.475
786.96
+ 0.43604
+ 0.97662
+ 98.965
-818.31
Significant at the 95% level.
Significant at the 90% level.
. . Significant at the 80% level.
NS Not significant.
81. 4415
1031.518
0.210560
0.49098
89.5003
1220.906
0.951302 NS
1.92
0.3166
2.26
0.5097
0. 547
0.76291
2.07085.
1.98910. .
1. 10575 NS
-0. 67024 NS
0.566
Notation: *
-vl
^3
78
2„
The acreage of Durum wheat as reported by the appropriate
services in the Department of Agriculture, and expressed
in 1000 hectares;
3„
The National total annual rainfall as reported by the World
Weather report at the end of each year.
The estimated yield response equations are summarized in the
table on the following page.
The estimated coefficients of rainfall are positive and significant, their standard errors small, and the explanatory power of rainfall is significant.
The estimated negative coefficients of acreage
reflect the fact that Tunisian farmers were allocating lower productivity lands
21
to wheat production.
The insignificant response of the
local varieties grown on these lands to fertilizer application is reflected in a negative coefficient of fertilizer.
The high Durbin-Watson
statistic indicates the absence of autocorrelation in the data used.
The Modern Production Period
The yield response model was fitted to time series data covering
the modern production period (1960-1974).
The data used included
the same items mentioned in the yield response model fitted to the
traditional production period.
21
The number of observations is 15.
More than two-thirds of the total acreage of wheat in the
country are composed of marginal and poorly structured lands.
Appendix Table 9.
The estimated Durum wheat yield response in the traditional production period.
Variables
Regression
Parameter
1
Constant
Total Annual
Rainfall
2.5576
+0.0056
0.84259
0.004103
3.03537
1.37769..
Constant
Total Annual
Rainfall
Acreage of D. W.
4.5998
+0.008375
1.26671
0.003911
3.63125
2.141510*
-0.00275
0.001374
-2.0050*
Constant
total Annual
Rainfall
Acreage of D. W.
Fertilizer
4.6984
+0.00870
1.37254
0.004260
3.4231
2.0425*
-0.00287
-0.02514
0.001499
0.09255
2
3
Notation: *
Coefficient
Significant at the 95% level.
Significant at the 90% level.
. . Significant at the 80% level.
NS Not significant.
1
D. W. = Durum wheat.
S. E.
t
-1.91618.
-0.27163 NS
Durbin-Watson
R
2
1.43
0.136
1.84
0.367
0.372
80
Three regression equations have been estimated on a stepwise basis.
The estimated yield response equations are summarized in the table
on the following page.
The estimated coefficients of rainfall are positive and significant,
their standard errors quite small, and the explanatory power of rainfall is significant.
The estimated coefficients of fertilizer are positive and significant, indicating a higher response of the new Durum wheat varieties,
recently introduced in the country, relative to the local varieties.
The negative coefficient of acreage, however, indicates that
the quality of the land devoted to wheat production in the country, is
still an important factor, although much less so than was the case
during the traditional period.
The absence of autocorrelation is re-
flected in a high Durbin-Watson statistic.
Appendix Tabl e 10.
Variables
Regression
The es timated Durum wheat yie:ld re sponse in the modern prodAuction pieriod.
Parameter
Co efficient
S. E.
t
Constant
Total Annual
Rainfall
1.013424
+0.013424
0.863507
0.00343857
1.74437
3.90395**
Constant
Total Annual
Rainfall
Fertilizer
1.3972
+0.01068
0.7892845
0.0034480
1.770227
3.098297**
+0.076441
0.0400549
1.908398.
Constant
Total Annual
Rainfall
Fertilizer
Acreage of
Durum Wheat
2.2686
+0.012260
1.38025
0.0040525
1.643607
3.02517**
+0.067247
-0.0013737
0.042423
0.00177008
1.585154. .
-0.77604 NS
Durbin- Watson
R2
0.539
1.812
0. 646
0.665
Notation: ** Highly Significant (at the 99% level).
Significant at the 90% level.
. . Significant at the 80% level.
NS Not significant.
oo