Economic reforms and agricultural supply response in Jamaica


Material Information

Economic reforms and agricultural supply response in Jamaica
Physical Description:
xvi, 192 leaves : ill. ; 29 cm.
Ballayram, 1950-
Publication Date:


Subjects / Keywords:
Agriculture and state -- Jamaica   ( lcsh )
Crops -- Jamaica   ( lcsh )
Economic policy -- Jamaica   ( lcsh )
Food and Resource Economics thesis, Ph.D   ( lcsh )
Dissertations, Academic -- Food and Resource Economics -- UF   ( lcsh )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )


Thesis (Ph.D.)--University of Florida, 2001.
Includes bibliographical references (leaves 183-191).
General Note:
General Note:
Statement of Responsibility:
by Ballayram.

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 026974320
oclc - 47260198
System ID:

Table of Contents
    Title Page
        Page i
        Page ii
        Page iii
    Table of Contents
        Page iv
        Page v
    List of Tables
        Page vi
        Page vii
        Page viii
    List of Illustrations
        Page ix
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    Chapter 1. Introduction
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    Chapter 2. Economic structure, growth, and policy reforms in the Jamaican economy, 1962-1999
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    Chapter 3. Methodological and empirical issues in economic reforms and supply response
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    Chapter 4. Empirical estimation of crop supply response
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    Chapter 5. Supply response and counterfactual analysis
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    Chapter 6. Conclusions and policy implications
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    Appendix A. Price of selected crops produced in Jamaica, 1962-1999
        Page 174
    Appendix B. Quantity of selected crops produced in Jamaica, 1962-1999 (metric tones)
        Page 175
    Appendix C. Selected economic statistics on Jamaica
        Page 176
    Appendix D. Diagnostic statistics for model specification and test statistics for cointegration
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    Biographical sketch
        Page 192
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Full Text








First, I would like to express my deepest gratitude to

my wife for all her support throughout my studies here at

the University of Florida. Her support in this process was

overwhelming and unselfish. My daughters were also very

understanding, supportive, and encouraging, and I thank

them sincerely for the sacrifices they had to make so that

I could complete my graduate studies. My parents and in-

laws (all now deceased) gave me encouragement and support,

both financial and otherwise, in my quest to achieve a

higher education. Without their love, confidence and moral

support, none of this would have been possible. I owe them

an eternal debt of gratitude, because their support came at

a time when the cost of higher education was far beyond the

reach which their economic resources could accommodate.

I would also like to express my deepest gratitude to

Dr. Carlton G. Davis, chairman of my supervisory committee.

He opened the door for me at the University of Florida, and

provided me with countless hours of individual attention

during my course of studies. On numerous occasions he went

beyond what would normally be the call of duty of an

academic supervisor, to provide me with the support that

enabled me to continue my studies.

I would also like to acknowledge the contributions

from the other members of my supervisory committee: Dr.

Robert Emerson, Dr. Clyde Kiker, Dr. Richard Kilmer and Dr.

David Denslow, who provided me with valuable suggestions

during the preparation of this dissertation.

I also benefited immensely, in my course of studies at

U.F., from discussions with Dr. Max Langham, Dr. Charles

Moss, Dr. Ronald Ward and Dr. James Seale, Jr.

Financial support from the Food and Resource Economics

Department is greatly acknowledged. Dr. Carlton Davis'

efforts in securing this funding for me are greatly


Finally, I wish to acknowledge the excellent computer

guidance and support services which Alex Heyman, Roger and

Laura Clemons, Ed Howard and Juan Carlos, of the Food and

Resource Economics Support Center, provided throughout my

studies here at U.F.




ACKNOWLEDGEMENTS ...... .................. ii

LIST OF TABLES ....... .................... vi


ABSTRACT . . . . . . . . . . .


1. INTRODUCTION ...... ...................

1.1 Background to Jamaica's Economic
Reforms ..... .................
1.2 Problem Statement and Study
Justification ... ................
1.3 Objectives of the Study .. ...........
1.4 Hypotheses ...............
1.5 Conceptual Issues ..... ............
1.6 Procedural and Methodological
Considerations ............
1.7 Summary ....... ..................


2.1 Structure of the Economy and
Economic Growth: An Overview ...
2.2 Output Trends and Policies in
Jamaican Agriculture ........
2.3 The Economic Reforms .........
2.4 Summary ....... ................


3.1 Review of the Economic Reform
Literature . . . . . . .

* . 26

* . 30
* . 38
* . 46

. . . ix

. xv


* 10
. 11
* 12.

* 20
* 22

Before-After Approach ....
With-Without Approach ....
Comparison of Simulations

Approach ....

3.2 Preliminary Issues in Modeling Supply
Response in Jamaica .. ...........
3.3 Error Correction Model ........
3.4 An Error Correction Model for Crop
Supply Response in Jamaica .....
3.5 The Data . . . . . . . .
3.6 Summary ....... ................


4.1 Motivations for Using Cointegration
Analysis . . . . . . .
4.2 Definition of Variables ............
4.3 Testing for Stationarity .......
4.4 Estimating Long-run Supply Response .
4.5 Analysis of Short-run Dynamics ....
4.6 Summary ....... ................


5.1 Before-After Analysis ... ..........
5.2 Counterfactual Analysis ............
5.3 Summary ....... ................


. . 75
. . 79
* . 87
* . 90
* . 106
. . 136

* . 137


. . 165


1962-1999 (J$) ..... ...............

. . 174

JAMAICA, 1962-1999 (METRIC TONES) .. ....... ..175



REFERENCES ......... ...................... 183

BIOGRAPHICAL SKETCH ....... .................. .192


. . . . 54




2.1 Sectoral Contribution to Real Gross
Domestic Product (Period Averages,
Percentages) ....... .................. 27

2.2 GDP and Sectoral Growth (1995=100)
(Percentage) ....... .................. 28

2.3 Growth Rates of Total Agricultural and
Broad Agricultural Aggregate Indexes ...... ..30

2.4 Composition of Agricultural Output
(J$M, 1995=100), Selected Years ... ......... .32

2.5 Agriculture Sub-sectors as a Percentage
of Total Agriculture (Period Averages).... . 32

2.6 Growth Rates of Agricultural Components
(Percentages) .................... ...... 34

2.7 Average Rates of Growth of Farmgate
and F.O.B. Prices, Output and the
Nominal Protection Coefficient (NPC)
for the Period 1970-78, Jamaica ... ......... .36

2.8 Net Barter Terms of Trade and Agricultural
Income Terms of Trade (1980=100)
(Period Averages) ...... ................ .38

2.9 Outcomes of Economic Reform Policies
in Jamaica, 1986 vs. 1995 .... ............ .45

3.1 Empirical Studies on Agriculture
Supply Responses in Jamaica ..........

4.1 Alternative (Substitute) Crops in Each ECM

4.2 Unit Root Tests--Prices and Quantities
in Levels ...... .................

. . 56

. . 84

. . 88

4.3 Unit Root Tests--Prices and Quantities
in First Difference ...... ............... ..89

4.4 Diagnostic Statistics for Residual
Tests for the Banana ECM .... ............ 91

4.5 Tests of Cointegration Rank for Banana ECM . . 95

4.6 Estimated Long-run and Adjustment
Coefficients, P's, a's--Banana ECM .. ....... ..96

4.7 Estimated Long-run and Adjustment
Coefficients, P's, a's for all Crops ........ ..100

4.8 Endogenous and Exogenous Variables in Crops'
Impulse Response Functions .... ........... .109

4.9 Responses of Banana Quantity to Shocks
in the Banana VAR ...... ............... 111

4.10 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Banana VAR ..... .............. .114

4.11 Responses of Quantity to Shocks in Exogenous
Variables ....... ................... 117

4.12 Summary of Forecast Error Variance in
Crop Quantities Explained by Variables
in the VAR (Percentage) .... ............ 119

4.13 Responses of Sugar Quantity to Shocks
in the Sugar VAR ...... ................ ..121

4.14 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Sugar VAR ..... .............. 121

4.15 Responses of Coffee Quantity to Shocks
in the Coffee VAR ..... ............... ..122

4.16 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Coffee VAR ..... .............. ..122

4.17 Responses of Pimento Quantity to Shocks
in the Pimento VAR ...... ............... ..123


4.18 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Pimento VAR .... ............. .123

4.19 Responses of Yam Quantity to Shocks
in the Yam VAR ....... ................. ..124

4.20 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Yam VAR ..... ............... ..124

4.21 Responses of Orange Quantity to Shocks
in the Orange VAR ..... . ......... ..125

4.22 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Orange VAR ..... .............. .125

4.23 Responses of Cocoa-bean Quantity to Shocks
in the Cocoa-bean VAR .... ............. .126

4.24 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Cocoa-bean VAR ..... ............ .126

4.25 Responses of Potato Quantity to Shocks
in the Potato VAR ...........

4.26 Variance Decomposition Percentage of One-
period and Three-period Forecast Error
Variance--Potato VAR ... ...........

5.1 Descriptive Price and Quantity Statistics
--1962-1979 and 1980-1999 .......

5.2 Descriptive Price and Quantity Statistics
--1975-1979 and 1980-1984 .......

5.3 Diagnostic Statistics for Forecasts of
Fitted Values .............

* . 127

* . 127

. .. 140

. . 141

. . 155

5.4 Estimated Long-run and Adjustment
Coefficients, P's, a's for all Crops,
1962-1979 . . . . . . . . .

5.5 Estimated Long-run and Adjustment
Coefficients, P's, a's for all Crops,
1980-1999 . . . . . . . . .

* 157




1.1 Conceptualization of the Jamaican
Agricultural Sector ...........

2.1 GDP and Sectoral Contribution to GDP
in Constant (1995) Dollars ............

2.2 GDP Growth (Percentage Change Over
Previous Year, 1995=100) ... ..........

2.3 Growth of Total Agriculture, Industry
and Services (Percentage Change Over
Previous Year, 1995=100) ... ..........

2.4 Total Agricultural Output Index (1995=100)

2.5 Output Indexes for Broad Agricultural
Aggregates (1995=100) ..........

2.6 Sub-sectors as a Proportion of Agriculture

2.7 Selected Economic Policy Reforms
in Jamaica, 1977-98 ...........

4.1 Residuals for Banana Price in Banana ECM .

4.2 Residuals for Banana Quantity in Banana ECM

4.3 Residuals for Sugar Price in Banana ECM .

4.4 Residuals for Wage in Banana ECM .........

4.5 Cross- and Autocorrelograms in Banana ECM .

4.6 Plot of Eigenvalues for the Banana ECM . .

4.7 Impulse Responses to an Innovation in Sugar
Price--Banana VAR ............


. . 14

. . 27

* . 29

* . 29

. . 31

. 31

* . 33

* . 43

* . 92

* . 92

* . 93

* . 93

* 94

* . 94

* . 112

4.8 Impulse Responses to an Innovation in
Fertilizer Price--Banana VAR ... ........

4.9 Impulse Responses to an Innovation in Wage
--Banana VAR . . . . . . .

4.10 Impulse Responses to an Innovation in
Banana Price--Banana VAR ... ..........

4.11 Impulse Responses to an Innovation in Banana
Quantity--Banana VAR ..... ...........

4.12 Impulse Responses to an Innovation in Sugar
Quantity--Sugar VAR .... ............

4.13 Impulse Responses to an Innovation in Coffee
Quantity--Coffee VAR .... ............

4.14 Impulse Responses to an Innovation in Pimento
Quantity--Pimento VAR .............

4.15 Impulse Responses to an Innovation in Banana
Price--Sugar VAR ..... ..............

. 112

. . 112

. . 112

. . 113

. . 113

. . 113

. . 113

. . 128

4.16 Impulse Responses to an Innovation in
Fertilizer Price--Sugar VAR .......

4.17 Impulse Responses to an Innovation in Wage
--Sugar VAR ........ ............

4.18 Impulse Responses to an Innovation in
Sugar Price--Sugar VAR .... ...........

4.19 Impulse Responses to an Innovation in Banana
Price--Coffee VAR ............

4.20 Impulse Responses to an Innovation in
Fertilizer Price--Coffee VAR ..........

4.21 Impulse Responses to an Innovation in Wage
--Coffee VAR .............

4.22 Impulse Responses to an Innovation in

Coffee Price--Coffee VAR

* . 128

* . 128

* . 128

* . 129

* . 129

* . 129

. ........ 129

4.23 Impulse Responses to an Innovation in Banana
Price--Pimento VAR ... .............

. . 130

4.24 Impulse Responses to an Innovation in
Fertilizer Price--Pimento VAR ... ......... .130

4.25 Impulse Responses to an Innovation in Wage
--Pimento VAR ...... ................. .130

4.26 Impulse Responses to an Innovation in
Pimento Price--Pimento VAR .... ........... .130

4.27 Impulse Responses to an Innovation in Cassava
Price--Yam VAR ....... ................. .131

4.28 Impulse Responses to an Innovation in
Fertilizer Price--Yam VAR .... ........... .131

4.29 Impulse Responses to an Innovation in Wage
--Yam VAR ....... ................... .131

4.30 Impulse Responses to an Innovation in
Yam Price--Yam VAR ...... ............... ..131

4.31 Impulse Responses to an Innovation in Yam
Quantity--Yam VAR ..... ............... ..132

4.32 Impulse Responses to an Innovation in Orange
Quantity--Orange VAR ...... ........... 132

4.33 Impulse Responses to an Innovation in Cocoa-
bean Quantity--Cocoa-bean VAR ... ......... .132

4.34 Impulse Responses to an Innovation in Potato
Quantity--Potato VAR ......... ......... 132

4.35 Impulse Responses to an Innovation in
Grapefruit Price--Orange VAR .... .......... .133

4.36 Impulse Responses to an Innovation in
Fertilizer Price--Orange VAR .... .......... .133

4.37 Impulse Responses to an Innovation in Wage
--Orange VAR ....... ................. 133

4.38 Impulse Responses to an Innovation in
Orange Price--Orange VAR .... ............ .133

4.39 Impulse Responses to an Innovation in Banana
Price--Cocoa-bean VAR ..... ............. 134


4.40 Impulse Responses to an Innovation in
Fertilizer Price--Cocoa-bean VAR ... ........ ..134

4.41 Impulse Responses to an Innovation in Wage
--Cocoa-bean VAR ...... ................ ..134

4.42 Impulse Responses to an Innovation in
Cocoa-bean Price--Cocoa-bean VAR ... ........ ..134

4.43 Impulse Responses to an Innovation in Cassava
Price--Potato VAR ..... ............... ..135

4.44 Impulse Responses to an Innovation in
Fertilizer Price--Potato VAR .... .......... .135

4.45 Impulse Responses to an Innovation in Wage
--Potato VAR ....... .................. .135

4.46 Impulse Responses to an Innovation in
Potato Price--Potato VAR ..... ............ .135

5.1 Nominal Price Changes--Banana (BANP)
and Sugar (SUGP) ...... ................ .143

5.2 Nominal Price Changes--Coffee (COFP)
and Pimento (PIMP) ...... ............... .143

5.3 Nominal Price Changes--Yam (YAMP)
and Orange (ORP) ...... ................ 143

5.4 Nominal Price Changes--Cocoa-bean (COBP)
and Potato (POTP) ..... ............... .143

5.5 Real Price Changes--Banana and Sugar
(1980=100) ....... ................... ..144

5.6 Real Price Changes--Coffee and Pimento
(1980=100) ....... ................... ..144

5.7 Real Price Changes--Yam and Orange
(1980=100) ....... ................... ..144

5.8 Real Price Changes--Cocoa-bean and Potato
(1980=100) ....... ................... ..144

5.9 Banana Quantity--Actual (LBANQ) and
Forecasted (FOLBANQ) ..... .............. .148


5.10 Banana Price--Actual (LBANPR) and
Forecasted (FOLBANPR) ..... ............. 148

5.11 Sugar Price--Actual (LSUGPR) and
Forecasted (FOLSUGPR) ..... ............. 148

5.12 Wage--Actual (LWAGE) and Forecasted
(FOLWAGE) ........ ................... 148

5.13 Fertilizer Price--Actual (LFERP) and
Forecasted (FOLFERP) ..... .............. .149

5.14 Sugar Quantity--Actual (LSUGQ) and
Forecasted (FOLSUGQ) ..... .............. .149

5.15 Coffee Quantity--Actual (LCOFQ) and
Forecasted (FOLCOFQ) ..... .............. .149

5.16 Coffee Price--Actual (LCOFPR) and
Forecasted (FOLCOFPR) ..... ............ 149

5.17 Pimento Quantity--Actual (LPIMQ) and
Forecasted (FOLPIMQ) ..... .............. .150

5.18 Pimento Price--Actual (LPIMPR) and
Forecasted (FOLPIMPR) ..... ............. 150

5.19 Yam Quantity--Actual (LYAMQ) and
Forecasted (FOLYAMQ) ..... .............. .150

5.20 Yam Price--Actual (LYAMPR) and
Forecasted (FOLYAMPR) ..... ............. 150

5.21 Cassava Price--Actual (LCASPR) and
Forecasted (FOLCASPR) ..... ............. 151

5.22 Orange Quantity--Actual (LORQ) and
Forecasted (FOLORQ) ..... .............. 151

5.23 Orange Price--Actual (LORPR) and
Forecasted (FOLORPR) ... ..........

5.24 Grapefruit Price--Actual (LGRPR) and
Forecasted (FOLGRPR) ... ..........

5.25 Cocoa-bean Quantity--Actual (LCOBQ) and
Forecasted (FOLCOBQ) ... ..........


. . . 151

. . . 151

. . . 152

5.26 Cocoa-bean Price--Actual (LCOBPR) and
Forecasted (FOLCOBPR) ..... ............. 152

5.27 Potato Quantity--Actual (LPOTQ) and
Forecasted (FOLPOTQ) ..... .............. .152

5.28 Potato Price--Actual (LPOTPR) and
Forecasted (FOLPOTPR) ...... .............. .152

5.29 Banana--Fitted Output for Reform Period
(BANFITA) and Counterfactual (BANFITC) ...... .161

5.30 Sugar--Fitted Output for Reform Period
(SUGFITA) and Counterfactual (SUGFITC) ...... ..161

5.31 Coffee--Fitted Output for Reform Period
(COFFITA) and Counterfactual (COFFITC) ...... ..161

5.32 Pimento--Fitted Output for Reform Period
(PIMFITA) and Counterfactual (PIMFITC) ...... .161

5.33 Yam--Fitted Output for Reform Period
(YAMFITA) and Counterfactual (YAMFITC) ...... .162

5.34 Orange--Fitted Output for Reform Period
(ORFITA) and Counterfactual (ORFITC) ........ ..162

5.35 Cocoa-bean--Fitted Output for Reform Period
(COBFITA) and Counterfactual (COBFITC) ...... ..162

5.36 Potato--Fitted Output for Reform Period
(POTFITA) and Counterfactual (POTFITC) ...... .162


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy




May 2001

Chairman: Dr. Carlton G. Davis
Major Department: Food and Resource Economics

A number of economic reform programs have been

undertaken in Jamaica, over the past two decades. Designed

largely by the International Monetary Fund (IMF) and the

World Bank, these reforms focused on correcting internal

policy weaknesses and creating an environment conducive to

sustained growth. The reforms emphasized liberal trade and

exchange rate regimes, a less intrusive and smaller public

sector, and reliance on market forces to determine

agricultural prices and quantities.

Against this background, this study investigates the

impact of these recent economic reforms on agricultural

crop supply responses in Jamaica. The estimation technique

used an error correction modeling framework based on


cointegration theory, within an estimation framework

developed by Johansen. The results of the crop supply

response estimation confirm that there is a long-run

relationship between agricultural crop output and price

incentives. Most of the estimated crop price elasticities

are low, statistically significant, and fall within the

range estimated by other studies on Jamaica. The adjustment

process of the short-run to the long-run was found to be

slow for some crops and higher for others.

Using a counterfactual, which assumed no change in

policy regime, fitted series of supply response functions

from the pre-reform period were forecasted within a

univariate ARMA(p,q) framework and compared to fitted

series of supply responses from the reform period. The

results are mixed. It was found that the impacts of the

economic reforms in Jamaica are crop and time specific.

Mean output was higher in the reform period for four of the

eight crops analyzed. Higher real price shifts were

observed in the reform period for some crops but these

price shifts were also accompanied by higher price-

variability. This suggests that the pro-competitive effects

that were expected to accompany the reforms may have

outweighed the stability impulses of administered prices in

the pre-reform era.



The past two decades have seen a shift in economic

policies throughout Latin American and Caribbean countries.

Generally, these policy changes have been in response to

debt crises, persistent payments-imbalances, and years of

negative and slow growth. By the 1990s a new orthodoxy on

development thinking could be discerned. This is manifested

in reductions in public sector activities and greater

reliance on private sector initiatives and market forces, a

departure from the policy regimes of the 1960s and 1970s.

In Jamaica, as elsewhere, the new orthodoxy has

influenced economic policies in agriculture. In particular,

policies have shifted away from far-reaching government

interventions and control, to increased reliance on market

signals to allocate resources and form prices. In addition,

economy-wide macro-economic policy changes have been made

which can potentially influence agricultural incentives,

income, and output. Designed largely by the International

Monetary Fund (IMF) and the World Bank in consultation with


the Government of Jamaica, these reforms' are expected to

favor Jamaican agriculture under the presumption by the

Bretton Woods institutions that previous policies severely

discriminated against the sector. (This point is elaborated

in Chapter 2, section 2.4). This study pertains to the

impacts that these economic policy reforms have on

agricultural supply responses in Jamaica, as the

agricultural sector emerges from a heavily regulated sector

to one that is more open2 and liberal. This chapter

discusses the problems that this study addresses.

1.1 Background to Jamaica's Economic Reforms

For purposes of this study, the reform period is

defined as the years 1980-1999, while the pre-reform period

is 1962-1979. The year 1962 is sufficiently far back to

facilitate a meaningful analysis of economic policies and

conditions that led up to the dramatic changes in policies

in the reform period. The reform period marks a re-

orientation of economic policy. This change arose from the

stabilization programs of the IMF in Jamaica in the late

1970s. It gathered momentum in the 1980s and 1990s in the

I In this study, "policy reforms," "economic policy reforms," "economic
reforms," and "structural reforms," are used interchangeably.
2 Openness is defined here in terms of trade/GDP ratio. A high
trade/GDP ratio can coexist with high import tariffs, export subsidies,
and non-tariff barriers, signaling a non-liberal trade regime.


form of structural adjustment programs cum reforms for

economic liberalization, under the direction of the IMF,

the World Bank and other leading external funding agencies,

notably the Inter-American Development Bank (IDB) and the

United States Agency for International Development (USAID).

In effect, therefore, for the purposes of this study,

economic reforms refer to the policies stipulated in the

stabilization and structural adjustment programs which

Jamaica has been pursuing since the late 1970s.

When the People's National Party (PNP) took office in

1972 under Prime Minister Michael Manley, it was under

pressure to keep its election campaign promises to increase

real wages and government spending, and to reduce social

inequalities. The responses of the new administration to

this situation, coupled with subsequent external and

domestic events, were to plunge the economy into a

sustained recession and major disequilibrium. During the

previous administration under the Jamaica Labor Party

(JLP), the performance of the economy was impressive. GDP

growth rates were positive and relatively high (5.1 percent

per annum over the 1960-1970 period), inflation was less

than five percent per annum and the balance of payments

showed modest surpluses (Jefferson, 1972; IMF, 1998). Over

the 1970-1980 period, however, real GDP declined by -0.9


percent. In fact, with the exception of a negligible 0.7

percent GDP growth in 1978, negative growth rates were

recorded for all other six years between 1974 and 1980.

Similarly, in the productive sectors, agricultural value-

added growth declined from 6.7 percent in 1970-1972 to -0.4

percent in 1973-1980. For these same periods, declines in

growth rates were recorded for services from 9.2 percent to

-0.08 percent, manufacturing from 6.7 percent to -4.2

percent, construction from 6.0 to -10.6 percent, and mining

from 13.2 percent to 1.3 percent, respectively (Singh,

1995; IMF, 1998).

The external account reflected the production crisis

described above. Between 1972 and 1980, the accumulated

deficit on the balance of payments was US$679.2 million,

compared to an accumulated surplus of US$95 million between

1960 and 1971 (Jamaica, Bank of Jamaica, 1985). Further,

the deficit on the current account increased almost three-

fold from US$570.2 million in 1962-1970 to US$1,620.0

million in 1972-1980, and the capital account became

negative in 1977, signaling capital flight. At the same

time, the dwindling net capital inflows could not match the

current account deficit. This depleted international

reserves, which plummeted sharply from US$103.1 million in

1972 to minus US$461 million in 1980 (Sharpley, 1984). The


foreign exchange shortage harmed the economy given its

relative openness and dependence on foreign intermediate


Finally, the inflation rate, which was 4.2 percent per

annum over the 1960-1970 period, recorded double-digit

rates throughout the following decade. Domestic prices, as

measured by the consumer price index, rose sharply,

recording an annual increase of 25 percent and 47 percent

over the 1974-1975 and 1978-1979 periods respectively

(Sharpley, 1984). By the late 1970s economic conditions had

deteriorated to such an extent that, when combined with

manifest signs of social distress (such as a dramatic

increase in violent crimes and emigration of skilled

workers), they generated a sense of instability and crises

(Stephens and Stephens, 1986; Kaufman, 1985).

The crises indicated a need for policy changes, and it

appears that the government was thinking along those lines

as reflected in a Stand-by Agreement it negotiated with the

IMF just before the December 1976 elections. The Agreement

included, inter alia, a wage freeze, fiscal restraint and a

currency devaluation of 20 to 40 percent (Boyd, 1988).

However, in the December 1976 election the PNP was returned

to office and the new administration promptly rejected the

IMF Stand-by Agreement as being inconsistent with the


mandate obtained in the recent election. Instead, and as a

way of avoiding agreements with the IMF (Boyd, 1988), and

after significant slippages in the external and domestic

accounts (Sharpley, 1984), the government implemented its

own adjustment policy measures in January 1977. These

included (Boyd, 1988)

(1) The reversal of the previous wage indexation policy;

(2) Implementation of import and exchange controls, a

dual exchange rate system and foreign exchange


(3) Suspension of foreign debts for 18 months; and,

(4) A search for funding from sympathetic governments.

However, it became increasingly clear to the

government that in order to attract foreign capital some

formal agreement with the IMF was necessary. In this

regard, the government signed three agreements with the IMF

between August 1977 and June 1979. The first was suspended

after four months for failure to meet the stipulated

quarterly tests. The second, signed in May 1978, was

pursued in all its aspects by the government for a year.

Although economic performance under this agreement was poor

(Sharpley, 1984; Boyd, 1988), it was re-negotiated in June

1979. However, the agreement collapsed in December 1979


after the government failed to meet the program's

performance criteria.

In 1980, in light of increasing social unrest,

continued slippages in the fiscal deficits and external

accounts, severe foreign exchange shortages, and rising

inflation (Sharpley, 1984; Boyd, 1988; Thomas, 1999), Prime

Minister Manley called a general election so that the

nation could decide on a path of economic development and

"what part the IMF should play; or whether it should play

any part at all" (Jamaica, API, Manley, 1980). Dubbed "the

IMF election", the October 1980 election was won by the

strongly pro-IMF JLP, led by Edward Seaga. Expectedly,

therefore, both the IMF and the government began

negotiations on funding and policies aimed at ameliorating

the country's economic and social crises.

The new administration relied heavily on funding from

external sources. Several loan agreements were negotiated

with the leading collaborating lending institutions, the

IMF, World Bank, IDB and USAID which have developed a

system of cross-conditionalities on their loans, given

their basic set of shared objectives on economic policies

and on Jamaica (Anderson and Witter, 1994).

The prescription by the IMF and the World Bank

(Fund/Bank) on how best to deal with the economic crisis in


Jamaica was a series of economic policy reforms. These

reforms went beyond the expenditure-switching and

expenditure-reducing policies which macroeconomic policy

would normally prescribe under these circumstances, to

include a built-in bias in favor of a more liberal economic

system. The latter aimed at, inter alia, fiscal discipline,

liberalizing the domestic market and the external trade

sector, privatizing of State Owned Enterprises (SOEs) and

other social services, and generally, greater reliance on

market signals to allocate resources. Over all, between

1981 and 1992, IMF financial support totaled US$1,036.9

million (under 10 agreements), and that of the World Bank

US$360.4 million (under 8 agreements).

1.2 Problem Statement and Study Justification

The cumulative effect of the reforms mentioned above

is that the Jamaican agricultural sector is now expected to

operate within an economic framework that differs vastly

from that of the 1960s and 1970s. Historically, the sector

has played an important role in the economy. Agricultural

output to GDP ratio is about eight percent, agricultural

food export in total export is approximately 20 percent,

and agriculture's share of the total labor force exceeds 26

percent (Davis et al., 1999). Given the importance of

agriculture in the economy, how the sector performs in this


new policy environment demands urgent attention. In this

study, agricultural sector performance is evaluated in

terms of crop supply responses. Quantitative analyses of

the impact of these reforms on Jamaican agricultural supply

responses are both scarce and generally not particularly

robust. In addition, the literature on similar economic

reforms in other countries suggests that the outcomes of

these reforms are ambiguous, which justifies more empirical

work (Khan, 1990).

Additionally, this study is justified on the following

grounds. First, the economic reforms have generated major

changes in the long-term prospects for the national economy

within which agriculture will operate. After two decades a

good set of data on these policy reforms is now available

which should facilitate empirical research on the impact of

these reforms on agricultural crop supply responses. This

evaluation can throw light on courses of action which

policy makers in Jamaica and elsewhere can consider as they

seek to reactivate and sustain long-term growth in the

agricultural sector.

Second, while a few studies have analyzed specific

aspects of the impact of the economic policy reforms on

Jamaican agriculture (Singh, 1995; Anderson and Witter,

1994; Newman and Le Franc, 1994; and Brown, 1994), what is


lacking is an over-all analytically rigorous assessment of

agricultural supply responses within the context of the new

policy framework as defined by the recent economic reforms.

Finally, analysis of the impact of these reforms on

agricultural supply responses is both timely and urgent in

light of an on-going debate. A number of writers in the

Caribbean and elsewhere have been advancing the view that

the kinds of economic reforms implemented in Jamaica and in

other countries have harmed agriculture (Anderson and

Witter, 1994; Green, 1989; Bates, 1989). In contrast a

recent series of studies sponsored by the World Bank

suggests that policy reforms similar to Jamaica's should

boost agriculture in countries which have traditionally

discriminated against the sector (Schiff and Vald6s, 1992a;

Krueger, 1992).

1.3 Objectives of the study

The general objective of this research is to evaluate

the impact of economic reforms on selected agricultural

crop supply responses in Jamaica over the 1980-1999 period.

The specific objectives are to provide

(1) A statistical evaluation of the performance of the

agricultural sector in the pre-reform (1962-1979)

and reform (1980-1999) periods.


(2) A descriptive, diagnostic and statistical analysis

of the economic reforms that have taken place over

the past two decades within the agricultural sector.

(3) An econometric (modeling) evaluation of selected

agricultural crop supply responses over the 1962-

1999 period, with the number and types of crops

chosen for study to be determined by data


(4) A comparative analysis of agricultural crop supply

responses in the reform period with a counter-

factual, the latter defined as crop supply responses

that would have resulted in the absence of the


1.4 Hypotheses

The following hypotheses are advanced in the study:

(1) Structural reforms significantly improve agri-

cultural supply responses.

(2) Sustained improvements in agricultural supply

responses require further broadening and deepening

of the reform process.

1.5 Conceptual Issues

Agriculture features prominently in policy discussions

when (1) it is believed that agricultural policies and

institutions help precipitate an economic problem which


policy makers are addressing; and (2) when agriculture is

an important contributor to employment, GDP, export

earnings, domestic food supply, and revenue for the

government (Binswanger and Deininger, 1997). Various

publications by the government of Jamaica suggest that both

of these factors have featured prominently in the recent

reforms, while (2) was a major consideration in the pre-

reform (1962-1979) period. Consequently, the conceptual-

ization is based on two perspectives that are believed to

have influenced the design of the policy reforms:

(1) The Jamaican government perspective. From numerous

government publications, it would appear that this

perspective is clustered around three main goals:

(a) increasing food supply; (b) developing rural

areas; and (c) increasing agriculture's contribution

to the over-all economy, through, inter alia,

employment, contribution to GDP, and export earn-

ings; and,

(2) The IMF/World Bank perspective, whose focus on the

agricultural sector clusters around (a) getting

prices right; (b) improving efficiency; and (c)

rationalizing public expenditure in the agricultural



These two perspectives are not mutually exclusive. On

the contrary, the choice of policies in a particular

program package results from extensive discussions between

officials of the IMF/World Bank and the Jamaican

government. The program policy mix therefore reflects the

particular economic situation in the country as well as the

preferences of the government (Khan, 1990). Despite this, a

review of the literature on Jamaican agricultural policy

formation suggests that since the late 1970s the influence

of the IMF/World Bank perspective has exceeded the Jamaican


Given the two perspectives mentioned above, and a

review of the content of the reforms since the late 1970s,

the evidence suggests that the reforms have focused on

three inter-related issues of relevance to the agricultural

sector: (i) agricultural (inter-sectoral) terms of trade;

(ii) agricultural growth, its adjustment, and supply

response; and (iii) efficiency in the agricultural sector

(Nallari, 1992; Singh, 1995; World Bank, 1996).

Figure 1.1 conceptualizes the Jamaican agricultural

sector, dividing the factors impacting agriculture into

external (e.g., world prices) and internal. The latter can

be separated into those that are exogenous (weather,

terrain) and those that are policy induced. Another useful

Policy Instruets:
P1. Agriculture Projects:
infrastructure, land
development, mechanization,
crop improvement
P2. Rural industries
P3. Monetary Policies: interest
rates, exchange rates.
P4. Tax Policies: income,
indirect, customs duties.
P5. Public consumption, rural
P6. Rural health, education,
P7. Import/Export controls,
tariffs, subsidies.
P8. Price controls, input
P9. Agriculture credit
PlO.Marketing: infrastructure,

Agriculture Sector
Performance Indicators:
1. Economic Outcomes
(a) quantity flows
supply response
agri. in GDP
agri. growth rate
(b) agri. multi-factor
(c) relative prices
2. Accumulation
coefficient of
capital formation
agri. employment
agri. tax revenues
rural nutrition
farm incomes

Figure 1.1:

Conceptualization of the Jamaican Agricultural



distinction is between prices and non-price factors

(including exogenous shocks) that influence agricultural

output and income. At the micro level, the price variables

include prices of the particular crops, prices of

alternative crops, input prices, and the general price

level. Government policies exercise both direct and

indirect influence on agricultural prices and thus on

agricultural performance. Direct (sectoral) policies such

as price ceilings, guaranteed prices and trade

taxes/subsidies provide incentives to shift resources among

crops and sectors of the economy (Binswanger, 1989).

Government policies also can influence output indirectly

through macroeconomic (or economy-wide) policies. The most

critical components in this regard are fiscal policies and

exchange rate policies (Mamingi, 1997).

The terms of trade as a policy variable turns on the

hypothesis that if all prices were determined in markets,

and effective rates of taxation were equalized across

commodities, then agriculture's supply responses, growth,

income, and contribution to GDP would be higher compared to

situations of negative effective protection of the sector

(Schiff and Vald~s, 1992b). A negative effective protection

of agriculture arises when:

(1.1)i Pf)+ 5 C,] < o

where P is a general price deflator, Pi denotes the producer

price of crop i, Pf is the free-market price for crop i,

and 8 is a subsidy to producers as a proportion of cost, Ci.

For many developing countries, agricultural pricing

policies have consistently kept Pi below P and subsidies

have not sufficiently counterbalanced this disparity

(Schiff and Vald6s, 1992b). Given severe budgetary

constraints, to achieve at least zero effective protection,

the policy implication of (1.1) is to raise the real


eliminating the disparity between Pi and P. In effect,

improving agriculture's terms of trade.

The exchange rate sets an upper limit on agricultural

export earnings and, when combined with input taxes and

subsidies, affects input prices and competing agricultural

imports. Changes in the real exchange rate can affect

agricultural output and growth by altering the terms of

trade between agriculture and non-agricultural sectors.

Further, policies that lead to over-valuation of the

exchange rate can adversely affect export crops, encourage


rent-seeking activities and generate unproductive uses of

resources (Jaeger, 1991).

In addition to the price policies, non-price factors

constitute an important influence on agricultural output.

These factors reflect the material conditions of production

in the agricultural sector. Some of these factors include,

inter alia, government expenditure and investment in the

agricultural sector, construction of rural infrastructure

(roads, drainage and irrigation works), extension services,

rural credit institutions, and dissemination of relevant

scientific information to farmers. The aim of agricultural

sector-specific programs is to find a mix of policies for

increasing efficiency and productivity in the sector. It is

assumed that these two outcomes are necessary (if not

sufficient) conditions for increasing agricultural output

and growth by reducing costs of production and/or

increasing product prices. These policies focus on using

public investment in agriculture efficiently, reducing

marketing and transport bottlenecks, improving agricultural

extension services, health and education (capital formation

in agriculture), rationalizing input prices, and enhancing

the efficiency of parastatals in the agriculture sector.

Behrman (1990) has advanced an important perspective

on the channels through which policies affect performance


indicators. He argues that analysis of the impact of policy

reforms on performance indicators must explicitly consider

the conduits through which the effects of the policies are

transmitted to the observed (or desired) outcome. These

"meso-level" variables, identified as markets (product,

input and financial) and infrastructure (economic and

social), are the interface between the policies (sector-

specific and economy-wide) and targets. In Figure 1.1, for

example, various policies, Pi, i = 1,2,3,...10, are

identified. Some are macroeconomic (e.g., monetary policies

and exchange rate adjustments), whereas others are sector

specific (e.g., agriculture credit, tariff reductions in

the trade sector and elimination of price controls in

agriculture). These policies are then combined to achieve

specific targets, either at the sectoral or macroeconomic


Behrman (1990) emphasizes, however, that the meso-

level variables condition the effectiveness of policies on

the target variables and that analyses of policy impacts

must also evaluate how policies have influenced these meso-

level variables. For example, if poor transportation, lack

of effective irrigation, or in-efficient research and

extension services restrain farmers' responses to higher


prices, then improving these meso-level variables may do

more for the farmer than price increases (Chhibber, 1989).

The influence of the factors mentioned above on

agricultural supply responses has been well documented in

the empirical literature. However, the recent economic

reforms have had an enduring effect on these factors. This

points to an important issue raised in the literature,

viz., how to measure the magnitude of reforms (IDB, 1997).

Economic statistics such as exchange rate differentials,

inflation rates, tax changes and so on deal with outcomes

rather than the policies that gave rise to them. In order

to address this issue, structural policy indexes have been

constructed by Lora (1997) and others.

The index by Lora (1997) was constructed for twenty

countries in Latin America and the Caribbean. This index

seeks to measure the extent of market freedom accorded to

economic policies in areas of trade, tax, finance,

privatization and labor. In each of these areas indices of

market freedom are identified. For example, in trade policy

the indices are average tariffs and tariff spreads; in tax

policy the indices include, inter alia, tax rates on

companies and on individuals; and on financial policy,

indices include freedom of interest rates on deposits,

loans, reserves on bank deposits, etc. (IDB, 1997). The

structural policy index is a simple average of the indices

in the five areas. The index can range from 0 to 1, based

on the worst and best observations respectively, on market

freedom in the country. Further, the index is an important

indicator of the extent to which countries are departing

from past ways of operating their economies. Jamaica's

structural policy index has shown continuous movement

towards market freedom, increasing from 0.426 in 1985 to

0.684 in 1995. These index values are higher than the

average reported for the twenty Latin American and

Caribbean countries in the sample (Lora, 1997).

1.6 Procedural and Methodological Considerations

In approaching the general and specific objectives of

the study, critical analysis of the Jamaican agricultural

sector's performance is first undertaken. To achieve the

general objectives and, more specifically, objectives (2),

(3) and (4), requires four specific tasks. The first task

is to identify and evaluate the structural reforms

undertaken since the late 1970s. Both the stabilization and

the structural reform policies are evaluated according to

their (1) theoretical bases; (2) breath of vision; and (3)

logical consistency. Second, supply response models are

developed and estimated. Finally, specific objective (4) is


addressed within the context of simulating an alternative

path to that of the reforms.

Any appraisal of the reforms must compare their

impacts not to the pre-reform indicators but rather to some

specified, hypothetical alternative. This requires some

simulation exercises. The idea here is to generate

simulated time series over the reform period for the

performance indicators. The simulated series then

constitute the counterfactual to which the actual outcomes

in the reform period are compared. For the counterfactuals,

at least three scenarios appear to be logical extensions.

Scenario 1 assumes that the policies pursued over the pre-

reform period continued into the reform period, i.e., that

the reforms over the 1980-1999 period were not instituted.

Scenario 2 assumes policies based on the Jamaican

government's critique of the IMF/World Bank programs were

implemented. Finally, Scenario 3 assumes that IMF/World

Bank assistance came with no conditionalities. These

components form the basis of the data series for the

simulation exercise.

The three scenarios appear logical and plausible

options given (1) the initial defiance by the government of

the mandated reforms in the late 1970s; (2) the frequent

failures to meet conditionality tests because the reforms


were not implemented; and (3) government's own protest-

ations over the years of what are considered "acceptable"

reforms. While numerous instances of disagreements exist

between the Jamaican government and the IMF/World bank with

respect to appropriate reform policies, the clearest

statement to this effect is captured in the following


Even though lender and borrower therefore shared the
common concern regarding the need for economic reform,
there is still much debate about appropriate social
policies and about the specific effects of
manipulating major economic variables such as exchange
rates and interest rates. This was illustrated by the
lengthy and tortuous negotiations between the
government of Jamaica and the IDB and World Bank on
the 1989-90 Agricultural Sector Adjustment Loan.
(Anderson and Witter, 1994, p.14)

1.7 Summary

It is generally believed that developing countries

have historically discriminated against their agricultural

sectors in favor of industrial development. It is further

felt that policies that reverse that discrimination should

boost agricultural output and income. Over the past two

decades far-reaching economic reforms have been undertaken

in Jamaica leading to a new economic framework within which

the agricultural sector must now operate. This study seeks

to assess the impact of these reforms on agriculture crop

supply responses, an undertaking that is both timely and


urgent given the importance of the sector in the economy

and the absence of rigorous analytical studies on the

Jamaican experience with these reforms.


It is useful, at the outset, to situate the discussions

in this chapter against the backdrop of three distinct

phases of economic policy that characterize the economic

history of Jamaica over the period 1962-1999. In the first

phase, 1962-1972, the Jamaica Labor Party (JLP) emphasized

free markets. However, Bonnick (1984) argues that despite

the rhetoric of economic liberalism, in reality the

government pursued an import-substitution (IS) strategy

based on protectionism, trade restrictions, and price


In the second phase, 1972-1980, the People's National

Party (PNP) under Prime Minister Michael Manley pursued

economic populism and state directed control (dirigisme) in

an effort to build democratic socialism. This phase was

marked by extensive government intervention, which included

nationalization of major industries, price controls, and

subsidization of basic foods and some agricultural imported

inputs. These policies made significant demands on national

resources and created a large bureaucratic economic



structure. Consequently, the government was unable to

respond to the crisis in the world economy in the mid-

1970s, and was forced to approach the IMF for stabilization

funding in 1977.

The third phase, 1980-present, is directly linked to

the policies of the previous phases, particularly the 1977

IMF stabilization funding. Phase three can be viewed as

having two sub-phases. The first is the return of the JLP

to government in 1980-1989 and the implementation of

various Fund/Bank stabilization and structural adjustment

programs. The second, 1989-present, marks the return to

government by the PNP, the continuation of the market led

policies of the preceding JLP administration, but more

importantly, the intensification of the country's commit-

ment to liberalization of the economy. The rest of this

chapter is organized as follows: Section 2.1 provides an

overview of the structure of the economy and its growth

performance. Section 2.2 highlights trends and policies in

the agriculture sector. Sector 2.3 describes the economic

reforms, and Section 2.4 provides a summary of issues

raised in this chapter.

2.1 Structure of the Economy and Economic Growth:
An Overview

The relative contribution of economic sectors to GDP in

Jamaica has not changed much over the past two decades. The

data presented in Table 2.1 and Figure 2.1 show that

agriculture's share has been fairly stable, ranging from an

average of 8.4 percent over the period 1969-1979 to 8.0

percent over 1990-1998. Although agricultural contribution

to GDP is lower than that of the other sectors, these

comparatively small percentage contributions are deceptive.

Davis et al. (1999) have shown that the sector plays an

important part in the country's employment, food

production, and foreign exchange earnings.

The industrial sector, which includes mining,

manufacturing and construction, contributed on average 39.1

percent to GDP in the period 1969-1979 but declined to 37.3

percent in 1990-1998. The manufacturing sub-sector also

shows a decline from 18.4 percent in 1969-1979 to 16.3

percent in 1990-1998. Finally, services constitute the

largest sector of the Jamaican economy, accounting for over

50 percent of GDP over the period 1969-1998. Its

contribution to real GDP has increased from 48.5 percent in

1969-1979 to 54.7 percent in 1990-1998.

Table 2.1: Sectoral Contribution to Real Gross Domestic
Product (Period Averages, Percentage).

1969-79 1980-89 1990-98 1969-98
Agriculture 8.4 6.4 8.0 7.6
Industry 39.1 34.5 37.3 37.0
Manufacturing 18.4 20.9 16.3 17.1
Services 48.5 59.1 54.7 53.9

Source: Computed using data from Jamaica, Pannlng
Institute of Jamaica (various issues).
Note: The 1998 data used were preliminary estimates.

1973 1977 1981 1985
Years 1969-1998

1989 1993 1997

--Real GDP ---Agri. -Indus. -*-Serv.

Figure 2.1: GDP and Sectoral Contribution to GDP in
Constant 1995 Dollars.

Real sectoral and GDP growth rates are estimated and

shown in Table 2.2. The estimation uses a log-linear model,

Yt = ao0 + P*Time + Et and corrected for autocorrelation

whenever it exists. Over the 1969-1998 period, growth rates

were positive but consistently low, while sub-period growth

reveal mixed results. GDP growth rates were just over two








Table 2.2: GDP and Sectoral Growth (1995=100)
1969-79 1980-89 1990-98 1969-98
GDP 2.3a 2.4b -0.2 I. 'M
Agriculture -0.3 1.1 2.3b 0.6b
Industry 0.9 4_._3_ 3 -3.8a 0.8a
Services 4.6a 0.1 2.4b 1.6a
Source: Computed using data from Jamaica, Planning
Institute of Jamaica (various issues).
Note: The 1998 data used were preliminary estimates.
aI b indicate statistical significance at the five
and 10 percent levels, respectively.

percent in the 1969-1979 and 1980-1989 periods. Services

growth was reduced from 4.6 percent over 1969-1979 to 2.4

percent over 1990-1998, and was insignificant over the

1980-1989 period. Industrial growth, which was 4.3 percent

in the 1980-1989 period, declined significantly to -3.8

percent over the 1990-1998 period. Agriculture growth over

the 1990-1998 period was 2.3 percent, compared to its

insignificant growth in the two previous sub-periods. Over

the entire 1969-1998 period agriculture and industry

recorded less than one percent growth, while GDP and

services grew just over one percent, respectively.

These periodic growth rates mask the highly volatile

annual growth rates in these economic series as shown in

Figures 2.2 and 2.3. Over the period 1969-1998, annual

growth rates for GDP ranged between -9.0 and 13.0 percent,

and were negative in 12 of the 30 years. For the



tit 5

e 0
54 -5


1970 1974 1978 1982 1986 1990 1994 1998
Years 1969-98

---GDP Growth

Figure 2.2: GDP Growth (Percentage Change Over Previous
Year, 1995-100).

30 A
20 A

4 10
54 -10
0 -20


1970 1974 1978 1982 1986 1990 1994 1998
Years 1969-98
----Agri. Growth mInd. Growth ----Ser. Growth

Figure 2.3: Growth of Total Agriculture, Industry and
Services (Percentage Change over Previous Year, 1995=100).

1969-1998 period, agriculture growth rates ranged between

-12.6 and 29.3 percent, and were negative in 15 years.


Similar annual volatilities characterize the industrial and

services growth rate series.

2.2 Output Trends and Policies in
Jamaican Agriculture

The growth rates of volume indexes for total

agriculture and broad aggregates (food, crops, livestock

and cereals) and graphs for these series are shown in Table

2.3 and Figures 2.4 and 2.5. With the exception of the

cereals index, which declined over 1971-1998 at an annual

rate of -3.2 percent, the other indexes grew but at less

than two percent over the 1971-1998 period.

Table 2.3: Growth Rates of Total Agricultural and
Broad Agricultural Aggregate Indexes.
1971-79 1980-89 1990-98 1971-98
Total Agriculture 1.6a 1.7 1.9a 1.7a
Food 1.6a 1.6 1. 9a 1.7a
Crops 2.6lb 1.5a -3.6 1.7a
Livestock 1.6a -16.5 0.7 1.3a
Cereals 16.9a -9.0 -4.5- -3.2]
Source: Computed using data from Food and Agriculture
Organization, FAO Production Yearbook (various issues).
aI b, indicate statistical significance at five and ten
percent levels, respectively.

The composition of agricultural output is shown in

Table 2.4. Export agriculture, domestic agriculture, and

livestock, forestry and fishing constitute the aggregative

components of agriculture in GDP. The data in Table 2.5 and

the graph in Figure 2.6 show that domestic agriculture

o 120

I i



0 1971 1976 1981 1986 1991 1996
Years 1971-98

-*-Total Agriculture

Figure 2.4: Total Agricultural Output Index (1995=100).

Figure 2.5: Output
Aggregates (1995=100).


for Broad Agricultural




H 50

o 1971 1976 1981 1986 1991 1996
Years 1971-1998

-Crops a.Livestock -nCereal --Food

Table 2.4: Composition of Agricultural Output
1995=100). Selected Years.

Source: uamaica, Pannlng

instLIUte 01 Jamaica

Table 2.5: Agriculture Sub-sectors as a Percentage of Total
Agriculture (Period Averaqes).

Source: Computed using data from Jamaica,
Institute of Jamaica (various issues).
Note: Figures in parentheses are standard deviation.




Agriculture Sub-sectors 1969-79 1980-89 1990-98 1969-98
23.47 15.95 11.21 7.29
Export Agriculture (5.50) (2.24) (1.46) (6.26)
44.78 57.21 68.79 56.13
Domestic Agriculture (5.32) (6.35) (3.62) (11.17)
Livestock, Forestry & 31.73 26.85 20.03 26.59
Fishing (1.35) (4.49) (2.50) (5.65)

and Sub-
sectors 1969 1975 1980 1985 1990 1995 1998
Total 95.9 105.9 101.3 72.2 104.4 154.4 120.4
Export 34.3 25.9 14.8 13.9 13.6 15.4 12.3
Sugar 22.6 17.7 9.9 7.8 9.2 9.4 7.9
Other 11.6 8.2 4.8 6.1 4.4 5.9 4.4
Domestic 33.0 47.1 56.9 38.0 66.2 114.5 82.8
Root 14.4 26.9 25.3 14.6 35.1 62.8 42.7
Other 18.6 20.2 31.7 23.4 31.1 51.7 40.1
Livestock, 28.6 32.9 29.5 20.3 24.6 24.5 25.3
Forestry &

0 1 I- i . . . 1 -
1969 1973 1977 1981 1985 1989 1993 1997
Years 1969-98
s-Export Agriculture
-n-Domestic Agriculture
---Livestock, Fishing & Forestry

Figure 2.6: Sub-sectors as a Proportion of Agriculture.

constitutes the largest proportion of total agriculture in

the 1969-1998 period and other sub-periods. In 1969-1979

the domestic agriculture sub-sector averaged 44.8 percent

in total agriculture and increased to 68.8 percent in 1990-

1998. Both of the other two sub-sectors, export agriculture

and livestock, forestry and fishing, have declined over the

period 1990-1998 compared to the two previous decades. In

terms of growth rates, Table 2.6 shows that domestic

agriculture and its sub-groups are the only sub-sectors

within the agri-sub-sector that have positive growth rates

over the 1969-1998 period. This has compensated somewhat

for the negative and low growth in the other agriculture







Table 2.6: Growth Rates of Agricultural Components
Agriculture Sub-sectors 1969-79 1980-89 1990-98 1969-98
Export Agriculture -4.4a -I. 3D -T. 1 -2. a
Sugar -4 2a -2.6a -5.4a -2.0a
Other main exports -4.6a 1.3 1.0 -2.7a
Domestic Agriculture 1.8 11.2a 25.6a 2.6a
Root crops -2.7 19.7a -1.2b 2.6b
Other domestic crops 4.0a 3.4b -145 2.7a
Livestock, forestry, & -1.5 -3.3a 0.1 -1.7a
fishing II I
Source: Computed using data from Jamaica, Planning
Institute of Jamaica (various issues).
a, b, indicate statistical significance at the five and ten
percent levels, respectively.

The stagnation of agriculture in Jamaica, which can be

inferred from the growth rates in Table 2.6 reflects, to a

large degree, the state of the agricultural sectors in many

less developing countries (LDCs). A plausible explanation

for this, is that the development literature in the 1950s

and 1960s viewed agriculture as a static sector, from which

resources could be shifted to promote industry, considered

as the dynamic sector. To a large extent, this view has

influenced the kinds of agricultural policies that have

been pursued in the past by LDCs. In this regard, Schiff

and Vald~s (1992a, p.59) state:

In many developing countries, the high rate of
agricultural taxation has been part of an explicit or
implicit policy of industrialization-led growth,
justified in part by the belief that industry was the
dynamic sector while agriculture was static and not
very responsive to incentives. That means that
economic growth could be accelerated by shifting


resources from agriculture to industry, by taxing
agriculture directly, and by protecting the industrial

Many governments in the developing countries have

intervened in their agricultural sectors, both directly

through agricultural sector policies, and indirectly,

through economy-wide policies such as industrial

protection. Direct interventions take numerous forms. Some

of these include procurement measures (e.g., government

marketing boards as sole buyers of agricultural output, and

suppliers of major agricultural input); quotas and direct

taxation on various agricultural export crops; subsidies on

farm credit and farm inputs; and quantitative restrictions

and tariffs on imported agricultural imports. While some of

the direct interventions have benefited agricultural

producers, some are tantamount to an implicit tax on

agriculture, depressing farmgate prices and farm incomes

below levels that would otherwise prevail (Schiff and

Vald6s, 1992a). Indirect forms of interventions affect

agricultural production incentives via macroeconomic

policies (e.g., overvaluation of the exchange rate) and

industrial protection policies (Krueger, 1992).

Various measures have been employed by the Jamaican

government to extract surpluses from the agricultural

sector. These include taxing agricultural exports,


controlling farmgate prices by the state marketing boards,

over valuating exchange rates and reducing internal

agricultural terms of trade relative to manufacturing.

Studies by Gafar (1980, 1997) and Pollard and Graham (1985)

strongly support this proposition. Table 2.7 shows that

Table 2.7: Average Rates of Growth of Farmgate and F.O.B.
Prices, Output and the Nominal Protection Coefficient (NPC)
for the Period 1970-1978, Jamaica.
Growth Rates (%)1970-78 a
Farmgate F.O.B. Nominal Protection
Commodities Prices Prices Output Coefficient b
Sugar Cane -1.25 4.13 -2.90 0.82
Banana 5.06 7.77 -7.43 0.77
Cocoa 1.64 14.06 -0.54 0.72
Coffee 9.80 8.34 2.02 0.61
Coconut 7.06 4.67 -21.00 n.a.
a Adapted from Pollard and Graham (1985), Table 2.
b Based on the data in Pollard and Graham (1985), Table 4
for 1970-1979. The NPC is defined as the ratio of farmgate
prices (PF) to F.O.B. prices (Pw) received minus marketing
and processing costs (C): NPC = PF / (Pw C).

over the 1970-1978 period, the nominal protection

coefficient (NPC), for Jamaican agriculture was less than

one, indicating the extent to which the sector was taxed.

For example, a NPC of 0.82 means that the commodity is

taxed at a rate of 18 percent. Subtracting one from the NPC

gives the nominal protection rate, NPR, which, according to

Table 2.7, is negative, suggesting that producers of the

crops reported were not supported, but were taxed instead.


It should be emphasized also, that developing countries

have a tendency to overvalue their domestic currencies, so

that the official exchange rates used to calculate the NPC

overstate internal prices. Hence government taxation of

agriculture is even greater than is usually captured by the

NPC (Gardner, 1987).

More recent data compiled for this study also support

the proposition that Jamaican agriculture has been taxed.

Table 2.8 reports on the net barter and income terms of

trade between agriculture and manufacturing for Jamaica.

The net barter terms of trade, N, is defined here as

N = L, where PA and PM are the price indexes of agriculture

and manufacturing, respectively. Values of N greater than

one indicate that prices of agricultural commodities have

risen relative to those in manufacturing (Tsakok, 1990).

The estimates in Table 2.8 reveal that over the 1966-1978

and 1989-1999 periods, the net barter terms of trade were

unfavorable to Jamaican agriculture, but were favorable

over the decade 1979-1988.

Although the net barter terms of trade may move

against agriculture, the sector can still increase its

purchasing power if agricultural output increases pro-

portionately more than the decrease in agricultural prices.


The purchasing power of agriculture is captured in the net

income terms of trade, I, estimated as: I = PA x QAI where QA

is the agricultural output index. The index I is therefore

the net barter terms of trade adjusted for marketed

amounts. Increases in I indicate a rising purchasing power

of agriculture for buying manufactured goods (Tsakok,

1990). The data in Table 2.8 suggest that agriculture's

ability to purchase manufactured goods have peaked in the

1979-1988 period.

Table 2.8: Not Barter Terms of Trade and Agricultural
Income Terms of Trade (1980=100; Period Averages).
1966-78 1979-88 1989-98
Net Barter Terms of Trade 0.60 1.39 0.86
Income Terms of Trade 58.20 159.18 134.03
Source: Compiled by author.

2.3 The Economic Reforms

After the late 1970s, Jamaica undertook major changes

in economic policies, both sector-specific and economy-

wide. These policy changes have been an integral part of

the conditionalities usually attached to program packages

by external funding agencies. The reforms vary in

intensity, both inter-temporally and in terms of the areas

in which policy reforms were enacted, such as foreign

trade, taxation, and liberalization measures. Underlying


the reforms has been a conviction by funding agencies that

freer markets allow for a more productive and efficient use

of scarce resources, a condition not necessarily accepted

uncritically by the Jamaican government. Nevertheless, a

number of market restrictions were eliminated, regulations

deemed necessary were simplified and made more transparent,

and private enterprises were encouraged. The most

conspicuous reforms were the liberalization efforts to

facilitate foreign trade and financing activities through

exchange rate and tariff adjustments.

The reform period, 1980-1999, has been punctuated by

successive IMF/World Bank stabilization and structural

adjustment programs, as well as programs financed by other

international funding agencies. The stabilization and

structural adjustment programs of the IMF and the World

Bank for Jamaica were developed as programs of policy

reforms, aimed at reversing, within a few years, the

economic crisis in the country. Three facets of this crisis

emphasized in the IMF/World Bank literature are structural

factors, external factors and poor domestic policies,

including an anti-agricultural bias in pricing policies.

However, it is a matter of public record that these

IMF/World Bank reforms have been resisted by the Jamaican

government at various times, and have been hotly debated in


the popular media regarding the social impacts of

externally imposed structural adjustment programs.

Despite this apparent dissatisfaction, the government

has utilized operational policies along the lines of those

prescribed by the Bretton Woods institutions. While in

principle the early reforms were aimed at stabilizing the

economy, from the outset there was a built-in bias in the

policies for a more liberalized economic system. For

example, the three year Extended Fund Facility (EFF), which

the Jamaican government signed with the IMF in May 1978,

contained specific conditions for exchange rate devaluation

as well as the liberalization of domestic prices (Boyd,

1988). More extensive economic reforms were advanced by the

new administration under Prime Minister Edward Seaga who

held office from 1980-1989.

Under the 1982 and 1983 structural adjustment

programs, quantitative restrictions (QR), on trade were

replaced by tariff equivalents, and by 1984 all QRs were

eliminated. Exchange rate devaluation was pursued in 1984-

1985, followed by the unification of the official and

parallel rates. At the same time, the government began to

reduce the public sector via the divestment of state owned

enterprises (SOEs).


The 1990s witnessed the most protracted reforms aimed

at deregulation and liberalization of the Jamaican economy.

The PNP, which took office in 1989 under Prime Minister

Michael Manley, had campaigned in the general elections on

a platform similar to the JLP, vowing to continue the JLP's

market oriented policies. This was an opportunity for a

fresh departure for the PNP, which was noted for its

previous support for democratic socialism and extensive

government intervention. Garrity (1996, p.52) argues that

...the Manley-led government made the decision in 1990
to truly embrace the market and proceed with economic
liberalization reforms. For Manley... [t]o continue the
reforms of the previous JLP government would not be
sufficient to bring about the needed structural
changes, nor were there sufficient resources to
continue the previous reforms....

Based on the limited available options, Manley's

commitment to the liberalization process represented a

turning point in state-society relations in Jamaica. In

particular, the administration sought an accommodative

pattern of governance between state and social actors by

energizing the private sector. In this sense, the

liberalization process can be viewed as "state-sponsored

disengagement from a command role in the economy ... and the

creation of an enabling environment for private sector-led

growth and development." (Garrity, 1996, p.52)


Against this background, the sectoral adjustment loan,

which the government signed with the World Bank in 1989,

focused on liberalizing the agriculture sector along the

following lines:

(1) Deregulation of the coffee and cocoa boards by 1990;

(2) Shifts in government focus from production and

markets to support services and infrastructure;

(3) Continuation of the divestment of agro-enterprises

(e.g., sugar);

(4) Elimination of subsidies on agricultural credit;

(5) Reduction of tariffs; and

(6) Elimination of the Generalized Food Subsidies;

As a result, by 1991 the generalized food subsidies

were eliminated, and complete liberalization of the

exchange market and credit interest rate were achieved.

Consequently, the overall liberalization process, since the

first agreement with the IMF in 1977, opened markets to

more competition and reduced the role of the public sector.

As would be expected, the conditions that accompanied

the loans from the Bretton Woods Institutions involved

reforms at both the macroeconomic and the sectoral levels.

Figure 2.7 is a schematic presentation of the kinds of

economic reforms and a partial list of specific tasks

undertaken since the late 1970s. For convenience, the

Domestic Fiscal Monetary/Fin. Trade Other
Deregulation Reforms Reforms Liberalization Reforms

UL goVL. 01 SUDSl].1es k ]rea.lon
assets on interest, Agriculti
New pricing loans and Credit Bi
system for food and Nati
coffee, Introduction DevelopmE
cocoa, of Bank
citrus and Generalized
pimento and Consumption
more Tax
sharing of

Figure 2.7: Selected Economic

Policy Reforms in Jamaica,


policy reforms are organized into five blocks: (1) Domestic

Deregulation; (2) Fiscal Reforms; (3) Monetary/Financial

Reforms; (4) Trade Liberalization and (5) Other Reforms.

Within each block, specific tasks are listed, reflecting

implicitly and explicitly policy changes, which seek to

enhance the role of market forces, encourage private sector

initiatives and reduce government regulation and

intervention in the economy. It is interesting to note that

in spite of intense criticisms regarding the reforms' lack

of success in producing the economic recovery predicted by

its proponents, the trend of economic reforms has not been

reversed in periods of economic stress. Such periods have

instead been met with the broadening and deepening of

reform efforts.

Table 2.9 shows selected economic statistics in the

pre-reform and reform periods in Jamaica. In the area of

trade, average tariffs in 1986 were 56 percent but fell to

11 percent in 1995. Exchange rate systems have been an

important policy instrument in Jamaica to establish

restrictions on capital outflows and restrictions for

repatriating export revenues and foreign exchange.

Following the exchange rate liberalization, many of these

restrictions have been dismantled. As evidence of the

process of exchange rate unification and deregulation,


Table 2.9 shows that the exchange rate differential (i.e.,

the difference between the average market price for foreign

exchange--inclusive of transaction costs and exchange rate

taxes--and the official rate) was 25 percent in 1986 but

fell to 5 percent in 1995.

Table 2.9: Outcomes of Economic Reform Policies in Jamaica,
1986 vs. 1995.
Maximum Tax Rate Policy
Tariff Exchange
Reduction Differential Companies Individuals Index, I
Net aver.
Tariffs % Percent Percent Percent 0 198611995 1986 1995 1986 11995 1986 1995 1985 1995
56 JF 25 5 45 32 50 25 0.402 0.684
Source: Adapted from IDB (1997).

In the area of tax reforms, Jamaica adopted various

changes aimed at administrative simplicity and ease of tax

collection. Taxes for companies were reduced from 45

percent in 1986 to 32 percent in 1995. The maximum taxes

for individuals were reduced from 50 percent to 25 percent

over the same period. Finally, the structural policy index,

which is a summary statistic of the extent to which market

forces are allowed to operate in the economy, increased

from 0.402 in 1985 to 0.684 in 1995.

2.4 Summary

The evidence presented in this chapter suggests that

the direction of change of economic structure of the

Jamaican economy that began around 1980 continued over the

past two decades. Over the period 1966-1998, growth rates

of GDP and economic sectors were low but positive. With few

exceptions, sectoral growth rates in the reform period,

1980-1999, were higher than in the pre-reform (1962-1979)


Some structural change within the agricultural sector

was discerned from the data. In particular, export

agriculture declined relative to other agri-sub-sectors.

Domestic agriculture recorded impressive growth, and it is

this agri-sub-sector's overall growth performance that

partially compensated for the negative and low growth in

the other agri-sub-sectors. Significant economic reforms

were implemented, and analysis of their impact on

agriculture will be undertaken in a later chapter.


The purpose of this chapter is four-fold. First, it

reviews the methods that have been used in the literature

to analyze the impact of economic reforms in developing

countries. Second, it reviews the literature on supply

response analysis. Third, it develops a crop supply

response model for Jamaica; and finally, it presents the

data sources for the analysis.

3.1 Review of the Economic Reform Literature

In this review of the economic reform literature two

sets of issues are addressed. First, attention is directed

at the way the economic reforms are conceptualized. Second,

the analytical methods used to evaluate the impact of the

reforms are examined.

One of the most challenging problems in capturing the

impact of economic reforms on target variables is how to

isolate the effect of each of the reforms undertaken. Since

the reforms were undertaken in various areas (trade

reforms, fiscal/monetary reforms, etc), at different points

in time, and with varying levels of intensities, their



effects on particular variables in the economy become

compounding and difficult to isolate. Khan (1990) argues

that it is theoretically and empirically difficult to link

all the policy reform measures to the ultimate targets of

the policies. Hence most studies have attempted to assess

the effects of the overall policy package on particular

target outcomes. This is the thrust of the studies by

Chadha et al. (1998), and some of the studies in Tshibaka

(1998), Campbell and Stein (1991), La Guerre (1994), Vald6s

and Muir-Leresche (1993), Commander (1989) and Weeks

(1995). In these studies, neither the precise nature of the

underlying economic relationships, nor the specific

policies adopted are made explicit. Instead, the attention

is on whether or not the program package, which in effect

gives rise to a particular policy environment, has been

"effective" in the sense of achieving broad macroeconomic

objectives (Khan, 1990).

Most of the studies reviewed proceeded from the

premise that the economic reforms originated from the

conditionalities that accompanied Fund/Bank-supported

packages. In all country experiences the problem of

economic instability provided the initial imperative to

seek IMF assistance, which, when it came took the form of

stabilization policies. However, in most of the studies


reviewed the stabilization policies are treated en passant,

or not at all, and instead attention is focused exclusively
on economic outcomes associated with structural adjustment

For most developing countries that have been pursuing

the Fund/Bank economic programs, the last decade has been

one in which the reforms have intensified the process of

liberalizing the economic system. A frequently raised

question with respect to Fund/Bank-supported structural

adjustment programs cum structural reforms for economic

liberalization, has been whether these programs are

effective in achieving stated economic objectives. A second

and related question is how to measure the effects of these

reform policies on the target variables identified in the

programs. With respect to this latter question, Guitidn

(1981) has argued that economic performance under a policy

package should be compared to a counterfactual. The latter

is defined as economic outcomes that would have taken place

in the absence of the program package. The concept of a

counterfactual is intuitively appealing and is a standard

yardstick widely used in economics to measure the impact of

policy interventions. Since the counterfactual is

3 Stabilization policies are designed to put the economy back on its
equilibrium path, whereas, structural adjustment policies aim at
putting the economy on a new (higher) equilibrium.


unobservable, it has to be estimated, hence alternative

methodologies used to evaluate the program effects are

judged in terms of their estimates of the counterfactual.

Although the preceding two questions have generated a

large body of literature over the past two decades, there

is little consensus in the economics profession either

about the impact of past programs on target variables, or

about how to estimate the effects of program packages

(Khan, 1990). With respect to measuring the impact of

reforms, there are three main approaches that have been

applied in the empirical literature. These are

(1) The before-after approach, which compares the

behavior of key macro-economic variables before and

during, or after, any particular reform period, or

policy package.

(2) The with-without approach compares the performance

of macro-economic variables of non-program countries

(the control group) with those from program

countries. A modified version of this approach is a

reduced form regression estimate that controls for

initial conditions in program and non-program


(3) The comparison-of-simulations approach. This

approach simulates performance of Fund/Bank-type


programs then compares them with simulated outcomes

from another set of policies.

Approaches (2) and (3) have been used extensively in cross-

country studies to assess the impact of Fund/Bank-supported

programs. The before-after approach has been the most

prevalent in country case studies using time series data.

3.1.1 Before-After Approach

The before-after approach has been the most popular in

the literature on Fund/Bank-support programs. Reichmann and

Stillson (1978) were the first to use this approach in an

examination of 79 Fund/Bank-supported programs over the

period 1963-1972. They compared growth, balance of payments

and inflation in the two years prior to and after the

implementation of the program. Connors (1979) also used the

before-after approach to evaluate 31 programs in 23

countries over the period 1973-1977. More recent studies

include Singh (1995) and the papers in Le Franc (1994), on

Jamaica. Similar studies on other developing countries

include most of the papers in Tshibaka (1998), Campbell and

Stein (1991), La Guerre (1994), Vald~s and Muir-Leresche

(1993), Commander (1989) and Weeks (1995).

The before-after approach is viewed by some analysts

as providing a relatively poor estimate of the counter-

factual to program effects by assuming that non-program

determinants of economic variables remain constant between

non-program and program periods. This assumption has been

questioned in the literature in light of the fact that non-

program determinants of economic outcomes (e.g., terms of

trade variations, changes in international interest rates,

weather, etc.) typically change year after year. Conse-

quently, Goldstein and Montiel (1986) have demonstrated

that the before-after estimates of program effects are

biased, since all economic changes in program period are

incorrectly attributed to program factors. These authors

suggested further that the before-after estimates are

unsystematic over time, since in any particular year

program effects will often be dominated by non-program

factors. For example, if a hurricane damages infra-

structural works and agricultural crops, then agricultural

growth may decline, causing all programs in that year to

appear to have performed poorly.

3.1.2 With-Without Approach

The with-without approach seeks to overcome the

shortcomings of the before-after approach by comparing

economic outcomes between program and non-program

countries. Since both groups of countries are subjected to

the similar external environments, it is argued that this

comparison cancels out the non-program determinants, so


that any observable differences in outcomes in the two

groups of countries are attributable to the Fund/Bank-

supported programs. In other words, the economic outcomes

observed in non-program countries are taken as the

counterfactual of what would have occurred in program

countries in the absence of Fund/Bank-supported programs.

Donovan (1981, 1982) was the first to use this

approach on a sample of Fund/Bank-supported programs

implemented between 1970-1980. Loxley (1984) also applied

this approach to 38 less developed economies (income of

$690 or less) with Fund/Bank program during 1971-1982.

Other similar studies include Gylfason (1987) and Pastor


A major problem with the with-without approach is that

countries in the sample of non-program and program

countries are not randomly selected. They are program

countries because of poor economic conditions prior to

entering into a Fund/Bank-support program. Consequently

there is a systematic difference between these two groups

of countries and the non-random selection of program

countries produces a biased estimate of program effects.

This is the result of attributing observable differences in

economic outcomes between program and non-program countries

to program status, when in fact the initial economic

position of the two groups of countries is an important

determinant of economic performance.

To overcome this problem requires identifying the

specific differences between program and non-program

countries in the pre-program period and controlling for

these differences prior to comparing economic outcomes.

This is the idea underlying a modified version of the with-

without approach. In this regard, Goldstein and Montiel

(1986) proposed a generalized evaluation estimator to

control for pre-program differences between program and

non-program countries. This estimator is a reduced-form

relationship that links changes in macroeconomic outcome

(program target variables) to lagged values of the target

variables, lagged values of policy variables and variables

that represent exogenous effects on the target variables.

These authors applied this approach to a sample of 58

developing countries in which 68 programs were implemented

over the period 1974-1981. The approach was extended by

Serieux (1999) to include the effect of democratization in

Fund/Bank-supported program countries.

3.1.3 Comparison of Simulations Approach

Finally, the simulation approach relies on simulations

of economic models to make inferences on hypothetical

outcomes of Fund/Bank-type policy packages. Khan and Knight


(1981), created a simulation using panel data for 29

developing countries in a dynamic econometric model. The

objective was to investigate the hypothetical effects of

pursuing a stabilization program with similar policy

characteristics as a Fund/Bank-supported one. The authors

later (Khan and Knight, 1985) extended their simulation

exercise to include comparisons of alternative packages.

More recent studies include Robinson and Gehlhar (1996),

and Chadha et al. (1998), who use computable general

equilibrium (CGE) models for the Egyptian and Indian

experiences with recent economic reforms, respectively.

3.2 Preliminary Issues in Modeling Supply
Response in Jamaica

A number of empirical studies have been conducted in

the past to estimate crop supply response in Jamaica. A

partial list of these studies is shown in Table 3.1. With

the exception of Gafar (1997), all of the studies were

conducted prior to the period 1980-1999. In addition, none

of the studies addressed the issue of the impact of

economic reforms on agricultural supply response.

One approach to capturing the long-run and short-run

changes in agriculture supply response is to use the

Nerlovian-type partial adjustment models. Both quantity and

prices can be modeled to adjust to their long-run or

equilibrium path, and the model is capable of estimating

Table 3.1: Empirical Studies on Agriculture
mme i,% Tnniminsk



both long-run and short-run parameters as well as the speed

of adjustment towards the long run equilibrium. A potential

complication in such an analysis of long-run and short-run

changes is that most economic time series data are non-

stationary and usually characterized by a unit root.

This means that the linear properties of the series

such as its mean and variance, are not constant over the

sample but change over time (Greene, 1993; Gujarati, 1995).

Nelson and Plosser (1982) have shown that the economic

implications of an economic time series that is

Crop/ Funct. Price Elasticity
Category Period Author & Year Form Short-run Long-run
Banana 1954-1972 Gafar (1980) Linear 0.16 0.57
1961-1979 Pollard & Graham log 0.49 -2.72
Cocoa 1954-1972 Gafar (1980) Linear 0.41 2.56
1961-1979 Pollard & Graham Log 0.74 0.76
Coffee 1953-1968 Williams (1972) Log 0.70 -0.80
1954-1972 Gafar (1980) Linear 0.92 1.15
1961-1979 Pollard & Graham Log 0.10 0.07
(1985) 1
Citrus 1961-1979 Pollard & Graham Log 0.24 -1.33
Sugar 1954-1972 Gafar (1980) Linear 0.17-0.29 0.31-0.7
1961-1979 Pollard & Graham log 0.24 1.41
Broad Agri.
Aggregates 1964-1990 Gafar (1997) log
Export 0.20 0.35
Domestic 0.15 1.08
Livestock 0.15 0.21
Forestry &
Fishing 0.02 0.21
Total Agri. 0.12 0.23
Source: Adapted from Gafar (1997, p.213).


characterized by a unit root are different from those of a

stationary process. In particular, an economic time series

with a unit root will have a permanent response consequent

upon any shock in the system. In contrast, a stationary

series will reflect only a transitory response. Therefore,

the response to economic reform policies is not simply a

"policy on", "policy off" or one-shot choice. Even if the

reforms were temporary, so long as the economic series

possesses a unit root, there will be a permanent response.

Non-stationarity of variables poses problems of

estimation of functional relationships using conventional

econometric methods. In the first place, Fuller (1976) has

shown that under non-stationarity the limiting distribution

of the asymptotic variance of the parameter estimates is

not finitely defined, hence the conventional t and F tests

are inappropriate. Secondly, non-stationarity gives rise to

spurious correlation among variables (Greene, 1993). In

macroeconomic time series it is not unusual to find that a

variable is non-stationary in its level4 but stationary in

first differences. In technical terms, if Yt is non-

stationary, but AYt (the first difference) is stationary,

then Yt is integrated of order one, i.e., Yt~I(1). If two

4 Data that have not been transformed in any way (such as logarithmic
transformation, first differences, etc.), are said to be in 'level'


series Yt and Xt are 1(1) then a linear combination of them,

e.g., Zt = Yt aXt may also be 1(1). However, there may also

exist, a value for a that ensures that Zt is stationary. In

such an event, the two series are said to be cointegrated,

and the cointegrating vector is denoted (1, a).

It is tempting to conclude that in order to estimate

meaningful relationships among non-stationary variables,

all that is necessary is to difference the variables until

they achieve stationarity and then estimate the

relationship. However, Johansen and Juselius (1990) argue

that unless the difference operator is also explicitly

applied to the error process, such differencing results in

loss of information. In this event, resorting only to

estimating the relationship in difference form captures

only the short-term effects, while the long-term

relationship among the variables is left undetected

(Nickell, 1985). Finally, differencing the economic series

may not be appropriate, such as when economic theory

postulates a relationship among variables in levels, not in

difference forms.

To overcome these problems, econometricians have

developed an approach known as error correction models

based on cointegration. Hylleberg and Mizon (1989, p.124)

claim that


...when estimating structural models it is our
experience from practical applications that the error
correction formulation provides an excellent framework
within which, it is possible to apply both the data
information and the information obtainable from
economic theory.

Error correction modeling requires two conditions

(1) All variables must be integrated to the same order,

i.e., Yi-I(d), where d is the number of times Y has

to be differenced to achieve stationarity; and,

(2) All variables must be cointegrated of order (d b),

where b>O.

The idea underlying cointegration is that one or more

linear combinations of non-stationary variables are

stationary. That is, cointegration approaches the station-

arity issue as linear combinations of economic series,

rather than by differencing the series. The implication of

this is that if a set of variables is cointegrated then,

following the Granger Representation Theorem (Fuller, 1985)

a valid error correction representation of the data exists.

In effect, then, cointegration is a test of existence of a

long-run relationship of variables that are integrated of

the same order (Greene, 1993; Gujarati, 1995). However, an

important feature of error correction models based on

cointegration is that the data in both levels and

differences are included, thereby facilitating investi-

gation of both short-run and long-run effects in the data.

3.3 Error Correction Model

The error correction model (ECM) can be derived from a

re-parameterization of an Autoregressive Distributed Lagged

(ADL) model (Hendry et al., 1984). Alternatively, the ECM

can be derived from the dynamic optimizing behavior of

economic agents. This latter approach is presented here.

Following Nickell (1985), suppose economic agents

optimize their behavior with respect to an inter-temporal

quadratic loss function:

(3.1) L = t Y Y 8

(Y- tsy*s- Yt+S-1 A

where Y* is the desired or long-run equilibrium value of Y

that the economic agent can control to minimize L,

conditional on information at time t, and subject to

movements in Y*. The discounting and weighting factors are

a, (OO), respectively.

Minimizing (3.1) with respect to Yt+s gives a second

order difference equation whose solution at time t is:

(3.2) Ayt = 02AYt + ( Pl)

[( + (1 X- (2)0 (aq1)N+ -
EI J t

where pi is the stable root (i.e., the root that is < 1)

from solving the characteristic equation of the general

Euler equation which was derived from minimizing (3.1).

Equation (3.2) is an optimal rule and has an error

correction term in brackets [.]; the coefficient (I-Ii) is

the speed of adjustment, i.e., the speed of closure to any

discrepancy between desired and actual values of Y. In the

error correction term in (3.2) the long-run target is a

convex combination of all target values from Y-, onwards.

Nickell (1985) has shown that when 02 = 0 in the loss

function (3.1) then equation (3.2) nests the forward-

looking partial adjustment model (PAM):

(3.3) AY = ( I %i ( tiNY$s }Yt-

It is important to note that the dynamic equation

(3.3) does not necessarily have to be of a standard PAM

type. To estimate (3.3) empirically requires the para-

meterization of Yj ,. One way is to model this sequence of

expected target values as a stochastic process such that

Yt.S are expressed in terms of current and lagged values and

substituted into (3.3). The resulting equation may not

necessarily result in a PAM. Indeed, Nickell demonstrates

that when


...we allow the target to follow anything more
complex than a first order autoregression, the
structural equation [3.3], which is fundamentally a
partial adjustment model, will reduce to an error
correction mechanism in terms of observable variables
(Nickell, 1985, p.124).

Suppose that the actual values of the series follow a

second order autoregressive scheme with a unit root and a


(3.4) Yt+s= g + PYts-1 + (1 P t+S-2 + Et+S

where s>O, et+, is white noise, and g is the drift. Denoting

the expected value with an (*), the expectation of (3.4)


(3.5) Y s = g + PYt+s-1 + (1 P t s-2

Following the derivations by Nickell (1985) and

Alogoskoufis and Smith (1991) the solution to the second-

order difference equation (3.5) is:

*.= yt-+1 0 4 A4
(3.6) Y = S2-- gs + ( - Y

Substituting (3.6) into (3.2) yields the decision rule in

the form:

(3.7) =y C + + +y + iii1 PIAY -y- - Y1)
(1 + cxp1( -F t3

where c =g( PX2 P0101 P1X1 (2) glcX1 -
(2 P)[1 + ai(1 P)] (2 PX plp)

Equation (3.7) is written in the form of an ECM. The

parameterization of Y* in terms of exogenous variables would

reflect the long-run cointegrating relationship. According

to Nickell (1985, p.124),

since it is almost a stylized fact that aggregate
quantity variables in economics follow second order
autoregression with a root close to unity, we may find
the error correction mechanism appearing in many
different contexts.

3.4 An Error Correction Model for Crop Supply
Response in Jamaica

The dynamically unrestricted version of the ECM in

(3.7) can be expressed as:

(3.8) = *0 + 1AQ + 2(Qtl Qt

where Qt is output in logarithm and Vo, *1, *2 are straight-

forward analogues of the intercept and coefficients in

(3.7). Generally, Q* is parameterized in terms of other

(weakly) exogenous variables. This parameterization shows

the long-run cointegrating relationship between the

exogenous variables and the dependent variable, Qt. Given

the unrestricted nature of (3.8) a wide range of possible

processes that describe the law of motion of Qt can be

accommodated. Following previous agricultural supply

response models, quantity supplied is postulated as a

function of the expected values of a set of variables that

are believed to capture agricultural incentives. These

exogenous variables are, the price of the crop, Pc, the

price of substitute crops, Psi, i=1,2... and the prices of


inputs. In this study, two inputs are considered,

fertilizer and labor, whose prices are denoted as F and W,

respectively. With these specifications of the exogenous

variables, the parameterization of the long-run equilibrium

supply function of the cth crop is:

(3.9) Q. + O + 02iPit + O + 04F +

c = l...n; i=1,2,...; t=l...T; et-iid(0,a).

where all variables are measured in logarithms (to

facilitate interpretation of estimated coefficients), and

have been previously defined. The superscript e denotes

expected value of the variables. Given the parameterization

in 3.9, the general error correction model, with all

variables as previously defined, can be written as:

(3.10) AQt = X0 + XIAQtI + X2Apt_1 + \31AP1,t + X4AWe_

+ X5AF t1 + X6(Q +
+ es I+A t- Qt-J +

To give empirical content to these models, the

specification of expected values must be addressed. Clearly

if economic agents had full information about the current

variables at the time they are set, then actual values of

the variables would be substituted for their expected

values. When this is not the case, some process of

expectations formation has to be assumed. The applied

literature on ECM has largely ignored issues of


expectations. Because of its simplicity in practice, actual

values are usually substituted for expected values. An

alternative to this procedure is to assume that crop and

input prices are determined by policy changes for one year

in advance. With this assumption, expectations about

current economic variables have to be based on information

that is available up to the end of the previous period,

(t- I). This can be expressed as:

(3.11) x=e =(XtjZj =

where Xt denotes the economic variable of interest, and 0 is

the information set available to the economic agent.

Previous studies of crop supply response in Jamaica

assumed naive expectation, based on past (simple) lagged or

polynomial lagged prices. Under rational expectations,

expected current and future prices of crops, wages and

inputs will reflect the generation process for these

explanatory-forcing variables. As noted previously, a

second order auto-regressive process with a unit root with

drift seems adequate to describe the process followed by

many economic series. The data on quantities, prices and

inputs for this study have been analyzed and found to

follow this process. Consequently, the expected prices of

crops and inputs are characterized as follows:

(3.12) <:"I-, = ao + a, '-, + 0 a, ,-

(3.13) P-, = bo + bIP.1 + (I bj)P. ,-

(3.14) Ft= co +cF-, +(1-c )F,

(3.15) Wt =do +dW.-1 +(-dl)W,.2

Using (3.8)-(3.15), the general error correction model for

the cth crop is:

2 2
(3.16) AQ ct = a0c + .,t6Q.,t-j + Y a2j c,t-J + E a3ik APi,t-k
jal k-1

2 2
+ a.lawt 1 + E (mA -. + ajQc 51pc (21psi

-83W, -840),, ;

where, i=1,2, all variables as previously defined, and the

random error term is suppressed.

The last term in (3.16) is the error correction term. In

the empirical estimation of the ECM (3.16), the error

correction term is usually specified as the residual from

the cointegrating relationship.

The Engle-Granger (1987) two-step method has been used

extensively in the applied literature to estimate the ECM

(3.16). However this method assumes that the cointegration

vector is unique. Except in the bivariate model, this

assumption may be violated in multivariate models. To test

for, and estimate multiple cointegrating vectors, Johansen

(1988) and Johansen and Juselius (1990) have devised an

appropriate method within the following framework. Define a


standard vector autoregressive (VAR) model with lag length

k as:

(3.17) Xt = i1x + H2Xt_2 + ... + [kXt-k + Et

t=l1..., T

where X is an Nxl vector of N endogenous variables, et-iid

(0,A) with dimension NxN. The long-run, or cointegrating

matrix is:
(3.18) I nI n2 nk = n

The number of distinct cointegrating vectors, r, which

exists between the variables of X, is given by Rank (n).

Most economic time series appear to be integrated to

the order of one, in which case, r N-1, where N is the

number of variables in the vector X. In the case of a

bivariate model, N=2, and therefore if the variables are

cointegrated, then there is a unique cointegrating vector.

The matrix n is then decomposed as:

(3.19) H = ap'

where I represents the matrix containing the r

cointegrating vector, and a is the matrix of weights with

which each cointegrating vector enters each of the

differenced X equations. A large a value implies that the

system will respond to any deviation from the long-run

equilibrium path with a rapid adjustment. If a's are zero


in some equations, this is a sign of a weak exogeneity,

implying that the variable does not respond to the

disequilibrium in the system. The parameters a and P form

an over-parameterization of the model. However, the space

spanned by P, sp(P), can be estimated, and shown to be the

empirical canonical variates of Xt-k with respect to AXt.

This is in effect the following theorem advanced by


The maximum likelihood estimator of the space spanned
by P is the space spanned by the r canonical variates
corresponding to the r largest squared canonical
correlations between the residuals of Xt-k and AXt
corrected for the effect of the lagged differences of
the X process. (Johansen, 1988, p.233)

Implementation of this theorem begins by re-para-

meterizing (3.17) (detailed derivations are in Johansen,

(1988) and Enders, (1995)), into the following error

correction model:

(3.20) AXt = FAXt- + --+ Fk-AXt-k+1 + FkXt-k + St

where F = -I + R1 + H2 + ... + Ili, i=l ...k

Without any loss of information, the ECM in (3.20) is

therefore a transformation of the VAR(k) model in equation

(3.17), and is expressed in first differences and augmented

by the error correction term, fkXt-k. The long-run equi-

librium or impact matrix is the matrix F, and is equivalent

to rI = a' 0 in (3.19). The rank of fl is the basis of


determining the number of cointegrating relationship

between the variables in the ECM (3.20). Johansen (1988)

identifies three possibilities with regards to Rank(l),

(1) rank(I) = 0. This means that the variables are not

cointegrated and the model is basically a VAR in

first differences.

(2) 0 < Rank(11) < p. In this case, the variables are

cointegrated and the number of cointegrating

relationship(s) is less than the number of

variables, p, in the model.

(3) rank() = p. This means that all variables are

stationary and the model is in effect a VAR in


The loglikelihood representation of (3.20) is:

(3.21) L ) =

I (Rot + P'R + a'R)

Johansen's procedure begins by regressing AXt on the lagged

differences of AXt and generating fitted residuals Rot, then

regressing Xt-k on the lagged differences and generating

fitted residuals, Rkt. These fitted residuals are then used

to construct the following product moment matrices:

(3.22) S= T 1 Rjt i, j = 0, k
Tj Rit


The product moment matrices (3.22) are then used to find

the cointegrating vectors by solving the determinant:

(3.23) 1xSkk SkOSOOSOkj = 0

This will yield the estimated eigenvalues (xi, ..., n) and

eigenvectors (vl,...,vn), which are normalized such that:

(3.24) V'SkkV = I

where V is the matrix of eigenvectors. The most significant

eigenvectors then constitute the r cointegrating vectors,


(3.25) 1 = V '"" "Vr)

Using (3.25), a is then estimated from (3.19).

The critical issue in all of this is to determine

which, and how many, of the eigenvectors in (3.24)

represent significant cointegrating relationships. First,

the 0 vectors that have the largest partial correlation

with AXt, conditional on the lags of AXt, are identified.

Second, the eigen vectors that correspond to the r largest

eigen values are chosen. Finally, to determine the value of

r the following test statistics suggested by Johansen

(1988) are employed:

(3.26) 1(q, n) = -T : ln(l X)

(3.27) 2(q, q + 1) = -Tln( q+1)


The null hypothesis HO: r~q is tested with (3.26), while

HO: r = q is tested against HI: r = q + 1 with (3.27). The

critical values for these tests are taken from Osterwald-

Lenum (1992). The critical values from this source

recalculates and extends those critical values from

Johansen (1988) and Johansen and Juselius (1990), to handle

a full test sequence from full rank (r = p, i.e., Xt is

stationary) to zero rank (r = 0, i.e., all linear

combinations of X are I(1)), for at most 11-dimensional


The cointegration technique is used to determine the

long-run relationships among variables. This co-movement of

variables in a long-run supply function has not been

explored for Jamaica. Cointegration analysis is appropriate

in this regard. It will also suggest which variables in the

supply function are in the long-run equilibrium.

3.5 The Data

The principal sources of annual time series data,

which are used in this study, are the Food and Agriculture

Organization (FAO) agricultural database (FAOSTAT), avail-

able on the internet, and annual publications of various

government agencies in Jamaica. These include, Economic and

Social Survey of Jamaica (Jamaica, Planning Institute of

Jamaica); Production Statistics (Jamaica, Statistical


Institute of Jamaica (STATIN)); Statistical Digest

(Jamaica, Bank of Jamaica), Statistical Year Book of

Jamaica (Jamaica, Statistical Institute of Jamaica

(STATIN)); Census of Agriculture, 1968, 1978, 1996

(Jamaica, Statistical Institute of Jamaica (STATIN));

International Financial Statistics (IMF); and data from

published and unpublished documents from the Ministry of

Agriculture in Jamaica.

It should be noted that the data on Jamaica contained

in the FAO database, FAOSTAT, IMF and World Bank sources

are based on publications and data supplied by STATIN,

Ministry of Agriculture, and other agencies of the

Government of Jamaica. The data used to estimate the supply

functions in this study are taken from the FAO FAOSTAT

database. This is the most comprehensive data set on crop

output and prices in Jamaica. However, in several areas the

data are less than ideal. For example, whenever data are

not available the FAO provides its own estimates based on

past crop performance, other crops and other country's

data. Jamaican officials claim that production data for

some crops reported on the FAO data base are not monitored

in Jamaica.

The crop output and price data are annual series, and

are collected at the farmgate through periodic production


surveys and agricultural censuses. Farmers in the Caribbean

rarely keep records of production, cost expenditures and so

on. Hence, for these farmers it is difficult to recall data

for production surveys that are conducted between long

periods. Consequently, this casts some amount of suspicion

on the reliability of the data. Nonetheless, these are the

data reported as official statistics, and are used by the

government as a basis for policy analysis/discussion.

Several important economic aggregates were not

adequately covered in the data sources. In particular, data

on agricultural wages are not available on Jamaica. As a

result, a proxy for this variable was constructed from data

on compensation to agricultural employees recorded in the

national accounts. Data on consumer price indexes--the

basis for deflating crop and input prices in this study--

were not available as continuous series over the 1962-1999

period. Consequently, a combination of splicing indexes and

converting the final 1962-1999 series to a 1980 base year

was undertaken.

Although the data are less than ideal in several

areas, and are bound to contain some noise, the advantages

of using them are:


(1) they are from a common source and are characterized

by a common accounting/estimating procedure in their

derivation; and

(2) the data are the most comprehensive time series

available on Jamaican crop supply in a single


3.6 Summary

There are competing approaches in the literature on

how to evaluate the impacts of economic reforms associated

with Fund/Bank-type policy packages. Each approach utilizes

the idea of a counterfactual against which actual economic

outcomes in the program period are compared. Estimating

crop supply responses over a period in which significant

policy changes have occurred, requires a modeling framework

that is capable of capturing both the long-run and short-

run changes. The Nerlovian-type supply response models have

been used in the literature for this purpose. However, in

the context of data series that are non-stationary, this

approach can produce spurious regressions. A more

appropriate analytical framework is that provided by error

correction models based on cointegration analysis.


The aim of this chapter is four-fold. First, the

central motivations for using error correction modeling

based on cointegration theory in this study are presented.

Second, the time-series data on prices and quantities to be

used in the ECMs to estimate crop supply responses in

Jamaica are tested for stationarity. Third, long-run supply

responses are estimated for eight agricultural crops.

Finally, the short-run dynamics of the crop supply

responses are analyzed.

4.1 Motivations for Using Cointegration Analysis

Chapter 3 provides a fairly elaborate treatment of the

theoretical and statistical aspects of error correction

modeling based on cointegration theory. Against that

background, it is useful to recall in a cryptic, condensed

and fairly non-technical way, the central motivations for

using this approach to address the issues with which this

study is concerned.

The empirical purpose of this study is to investigate

the impact of economic reforms on crop supply responses in


Jamaica. Generally, supply response models in agriculture

postulate a long-run relationship between output and

agricultural incentives (Askari and Cummings, 1976).

Deviations from this long-run equilibrium occur in the

short-run and may involve considerable adjustment costs to

the economic agent. This is especially the case when

significant policy changes are implemented. Jamaica

provides a good case for evaluating the connections between

economic reforms and supply responses. The country has

traditionally been heavily dependent upon agriculture for

food, employment and export earnings. A combination of

excesses in state intervention and adverse world economic

conditions prompted major economic reforms in the late

1970s in the form of serious macroeconomic stabilization

policies under the direction of the IMF.

During the early 1980s more far-ranging structural

reforms were instituted in an effort to reverse the current

account and fiscal deficits, reduce inflation and monetary

growth to achieve financial stability, restore economic

growth, and so on. Implicitly in these early reforms, but

more explicitly in the late 1980s and throughout the 1990s,

the aim has been to re-orient the economy towards a more

liberal economic system. These reforms took expression in

progressive devaluation of the Jamaican dollar, elimination


of state marketing boards, liberalization of agricultural

input and output prices and privatization of state held

monopolies and public enterprises. Intuitively, therefore,

the analysis of supply responses in these situations would

require a modeling framework that is capable of incor-

porating both the long-run and short-run changes.

A preliminary analysis of the Jamaican crop output and

price data series over the 1962-1999 period reveals sub-

stantial fluctuations, especially since the early 1980s.

The strongly time trended data imply a statistical problem

that has not been addressed in applied analysis on Jamaican

crop supply responses. This statistical problem is referred

to, in the literature, as non-stationarity of the time


The analytical approach chosen in this study to deal

with the above mentioned issues, emphases the importance of

considering the interactions between the variables in the

system in a simultaneous equation model, and to distinguish

between the short-run and long-run effects. The modeling

approach differs from those previously used to model

Jamaican crop supply responses in two very important ways.

First, the data are analyzed as a full system of equations.

This allows for possible interactions in determining the

precise relationships among the variables in the system.


Second, the multivariate cointegration modeling which

is used in this study, is designed for this type of

empirical work by explicitly classifying the non-stationary

and stationary components and facilitating an inter-

pretation in terms of the dynamics of short-run and long-

run effects. There are two general motivations for using

error correction models based on cointegration theory in

applied economic analyses. First, when time-series data are

non-stationary, i.e., their linear properties, such as mean

and variance, are time dependent, then conventional

econometric analysis on such data may produce "spurious"


Second, even though a set of time series may

individually be non-stationary, there may be a linear

combination among them that is stationary. Such series are

said to be cointegrated, that is, they have a tendency to

move together in the long-run, even though in the short-run

they may diverge from each other. This co-movement of

related series suggests the existence of long-run

relationship between them. So when data are non-stationary

there is the additional possibility that the data

generating process contains information about the

equilibrium process that makes the process adjust toward

the long-run steady state or the equilibrium path.


There is, therefore, additional economic insights

gained from the recognition that the data are non-

stationary. The component FkXt-1, (=- ap'Xt-i, since II = ap'),

in equation (3.20), is directly related to the non-

stationarity in the data. Since this component contains

information about the speed of adjustment, a, to some long-

run relations, P'Xt, and if the data are cointegrated, then

the economic process can generally be understood within a

theoretical model that assumes some adjustment behavior.

This means that theoretical models such as the partial

adjustment model (PAM), which assume static equilibrium,

cannot be used when data are non-stationary.

4.2 Definition of Variables

In this chapter, error correction models based on

cointegration theory are used to test the hypothesis that

long-run relationships exist between crop output and price

incentives in Jamaica. The estimation procedure is based on

the work of Johansen (1988) and Johansen and Juselius

(1990). There are basically three steps in this estimation


(1) test the order of integration of the variables and

specify the lag length of the variables using a

standard vector auto-regressive (VAR) specification.


(2) estimate the ECM and the number of cointegrating

relationship(s) among the variables included in the


(3) perform short-run analysis by conducting innovation

accounting on the ECM.

For each crop a p-variable vector autoregression (VAR)

of lag k is specified. The model is re-parameterized into

an error correction model (ECM) as specified in equation

(3.20) and estimated according to the methodology of

Johansen (1988) and Johansen and Juselius (1990). Esti-

mation is done using the Regression Analysis for Time

Series (RATS), version 4.3 (Doan, 1996), and Cointegration

Analysis for Time Series (CATS) in RATS, (Hansen and

Juselius, 1995), computer programs. The variables in each

ECM include the output (quantity) of the crop of interest,

the price of the crop, the price of a substitute (or

alternative) crop, and two input prices, average agri-

cultural wage rate and average fertilizer price.

The choice of a crop price variable is critical for

the estimation of crop supply responses. In this regard,

Askari and Cummings (1976) suggest using any one of the

following prices:

(1) Nominal farmgate price;

(2) Farmgate price deflated by any one of the following:

(a) a price index of farmer's inputs;

(b) a consumer price index; and

(c) some index of the prices of competitive crops (or

the price of the most competitive crop).

An additional issue that is related to the choice of

an appropriate price variable for the crop supply functions

especially within the context of the IMF/World Bank

programs in Jamaica, is that agricultural price incentives

are influenced by various macroeconomic policies. Of

particular importance, in this regard, is the real exchange

rate (RER), defined as the ratio of prices of tradable (PT)

to non-tradable (PN) goods (Tsakok, 1990). Krueger (1992)

and Schiff and Vald6s (1992a, 1992b), have shown

extensively how macroeconomic policies in developing

countries generally have a RER effect, which ultimately

affect output price and agricultural supply. In the

empirical literature the RER is usually approximated as

RER=e*WPI/CPI, where WPI is the foreign wholesale price

index, CPI is the domestic consumer price index, and e is

the official exchange rate. The World Bank's approach to

showing the link between macroeconomic policies (as

represented by the RER) and real crop prices, decomposes

real producer price as follows:



where RPP is real producer price, PF is the farmgate

producer price, PB is the border price, NPC is the nominal

protection coefficient, and PB is the real border price of

the country's exports (World Bank, 1994). This definition

of RPP shows that it contains information on the RER and

also reveals that it is really hazardous to include both

the RER and RPP in the same equation (Mamingi, 1997).

In addition to the issues raised above, two additional

considerations were taken into account in the choice of the

crop price variable. First, since farm producers sell most

of their marketable surplus immediately after reaping,

farmgate prices seem to be a good approximation for prices

received. Second, since farmers purchase most of their

requirements from retail markets, the consumer price index

seems to be an appropriate deflator for producer prices.

For these reasons, therefore, the farmgate price deflated

by the CPI was used as the real producer price (RPP)

variable in the supply functions. In effect, this price

variable reflects not only price incentives to the

producers, but also macroeconomic (reform) policies (as

represented by the RER). In particular, this link between

the price variable and macroeconomic policies is important

in order to pursue an investigation of the hypotheses

advanced on page 11.


The question regarding which alternative (or

substitute) crop to include in a particular crop's ECM

proved to be difficult. In the absence of recorded data on

this issue, the final choice of the substitute crop

resulted from a consideration of a number of factors. Among

these were, the nature of the crops (traditional export

versus domestic crops); the terrain where the crops are

grown (mountainous versus flat lands); tree-crops versus

annuals; and, root-crops versus vine-crops. The difficulty

of identifying an appropriate substitute crop (or crops)

can be demonstrated in the case of banana. Possible

substitute crops for banana are coffee and sugar, since

these are all traditional export crops. Banana is grown

extensively on flat lands, but is also cultivated on hilly

terrains as is coffee, whereas, sugar growing has been

confined to the relatively flat plains in Jamaica. Hence,

both sugar and coffee are plausible substitutes for banana,

and the choice of either one or both becomes an empirical


A further complication in the choice of a substitute

crop arises. In the early 1990s, this researcher observed

two cases where lands which were previously used to

cultivate sugar and banana were converted into papaya

groves. Telephone interviews conducted with officials of

the Ministry of Agriculture, Government of Jamaica,

indicate that these are not isolated cases, and that

similar land conversions have been observed into cut-

flowers, decorative foliage, aloe-vera, ochro, and other

non-traditional export crops.

Several substitute crops were initially included in

each ECM but in all cases it was found that the inclusion

of only one substitute crop price improved the statistical

properties of the model. The alternative crops in each

crop's ECM are reported in Table 4.1.

Table 4.1: Alternative (Substitute) Crops in Each ECM.
Crop Alternative Crops Considered
Banana Sugar coffee, papaya
Sugar Banana papaya
Coffee Banana', pimento, sugar, orange
Pimento Banana', coffee, cocoa bean
Yam Cassava potato, sweet potato
Orange Grapefruit', tangerine, coffee
Cocoa Bean Banana, pimento, coffee
Potato Cassava', yam, sweet potato
Crop chosen as substitute crop.

Two input prices are included in each crop's ECM,

namely, fertilizer price and average wage in the

agriculture sector. The fertilizer price variable is a

weighted price index of all types of fertilizers imported

into Jamaica, with quantities as weights. With respect to

the wage variable, there are no data on agriculture wages