Export Taxes and Their Effects on Farmers' Profitability and Risk in Argentina

171 Pages·2016·5.53 MB·English

University of Nebraska - Lincoln
DigitalCommons@University of Nebraska - Lincoln
Dissertations and Theses in Agricultural Economics Agricultural Economics Department
Summer 7-27-2015
Export Taxes and Their Effects on Farmers'
Profitability and Risk in Argentina
Ezequiel M. Villamil
University of Nebraska-Lincoln, [email protected]
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“EXPORT TAXES AND THEIR EFFECTS ON FARMERS’ PROFITABILITY
AND RISK IN ARGENTINA”
by
Ezequiel María Villamil

A THESIS

Presented to the Faculty of
The Graduate College at the University of Nebraska
In Partial Fulfillment of Requirements
For the Degree of Master of Science

Major: Agricultural Economics

Under the Supervision of Professor Fabio L. Mattos
Lincoln, Nebraska
July, 2015
EXPORT TAXES AND THEIR EFFECTS ON FARMERS’ PROFITABILITY AND
RISK IN ARGENTINA
Ezequiel María Villamil, M.S.
University of Nebraska, 2015

Adviser: Fabio L. Mattos
This main objective of this thesis is to analyze the effects of export taxes on the risk
faced by farmers in different regions of Argentina in their cropping operations for wheat,
sunflower, soybeans and corn. In the first chapter we introduce the variables and explain the
agricultural environment in Argentina. A set of three profit function models with different
export tax policies were specified in a Monte Carlo simulation template using data from 1985
to the present. A set of risk measures for the upper and lower partial moments along with the
overall probability distribution statistics are used to asses profit risk on each simulation
output for the three models. It was found that the model with variable-rate export tax
modestly reduces the downside risk while increasing the upside dispersion offering larger
profit opportunities. For the fixed-rate export tax model the probability of low partial moment
about zero has more mass, especially in the marginal regions. The model without export tax
shows overall positive means and more mass on the upside of the distribution as expected.
Comparison of results with normal distributions for the input variables with those from
distributions that fit the data the best showed that there is not a clear pattern, however the
differences could be significant given that the probability mass could shift to the other side
of the benchmark established at zero profits and therefore could affect farmers’ management
strategies.
iii

Dedication
In dedication to my lovely wife Angeles and my newly born son Facundo María who
encouraged and believed in me. They made this voyage possible and endured with me during
this beautiful experience at Lincoln, Nebraska. They deserve all the credit and all my love.
iv

Acknowledgement
The thesis would have not reached fruitful coast without the expert and professional
knowledge of my dearest Advisor Professor Fabio Mattos, who inspired and gave me third
thoughts on how to solve problems though out the last year.
Thanks to Professor Wes Peterson who shared with me his personal ideas and gave
his time to be part of the committee member. To Professor Azzeddine Azzam who so much
touch me during my Master’s program and for being so attentive to Agriculture Economics
student’s perspective and opinions.
Thanks to Professor Lilyan Fulginiti and Professor Richard Perrin who believed in my
capacity and accepted my application to the UNL Agriculture Economics Program.
Thanks to the University of Nebraska, Department of Agriculture Economics and its
Faculty members and Staff who so much touch me throughout the last two years.
Thanks to the Magazine “Margenes Agropecuarios” and Staff who submitted precious
data for my research which could not have been done without it.
Thanks to my friends and colleagues in Lincoln who assisted me during my studies
and shared with me beautiful moments.
v

Grant acknowledgement
This thesis is also the result of the effort implemented by BEC-AR program and staff,
as part of the Argentinian Presidential Fellowship, Argentina Presidential Cabinet, which
funded my Master in Sciences at the University of Nebraska. I must also acknowledge the
Argentine Fulbright Commission for all their support and organization as my sponsor in the
United States.
vi

1) TABLE OF CONTENTS
1) CHAPTER 1 - INTRODUCTION .................................................................. 1
1.1. STATEMENT OF THE PROBLEM ........................................................................................................ 1
1.2. OBJECTIVES .................................................................................................................................... 7
1.3. SCOPE AND SIGNIFICANCE OF EXPECTED OUTCOMES ...................................................................... 9
1.4. OVERVIEW OF DATA AND RESEARCH METHOD ...............................................................................10
2) CHAPTER 2 -THEORETICAL BACKGROUND ..................................... 12
3) CHAPTER 3 - LITERATURE REVIEW ................................................... 18
3.1. PAST STUDIES ................................................................................................................................18
3.2. AGRICULTURE AND THE ECONOMY IN ARGENTINA .......................................................................27
3.2.1. Overview ........................................................................................................................... 27
3.2.2. Recent History and Events ................................................................................................ 32
3.2.3. The Export Taxes:............................................................................................................. 35
4) CHAPTER 4 - DATA .................................................................................... 48
4.1. RESEARCH GEOGRAPHICAL SCOPE .................................................................................................56
5) CHAPTER 5 - METHODOLOGY AND RESEARCH PLAN .................. 58
5.1. FRAMEWORK AND MODEL APPROXIMATION ..................................................................................58
5.1.1. Profit (π) function ............................................................................................................. 59
vii

5.2. RESEARCH METHOD .......................................................................................................................61
6) CHAPTER 6 - RESULTS AND DISCUSSION .......................................... 69
6.1. SAME COMMODITY, ACROSS REGIONS AND ACROSS SIMULATION MODELS ....................................69
6.1.1. Corn .................................................................................................................................. 69
6.1.2. Soybeans ........................................................................................................................... 73
6.1.3. Sunflower .......................................................................................................................... 78
6.1.4. Wheat ................................................................................................................................ 82
6.2. OVERALL RESULTS ........................................................................................................................88
6.3. RESULT COMPARISONS BETWEEN SIMULATIONS USING FITTED DISTRIBUTIONS AND SIMULATIONS
ASSUMING NORMALITY OF RANDOM VARIABLES. ..............................................................................................90
6.3.1. Corn .................................................................................................................................. 90
6.3.2. Soybeans ........................................................................................................................... 92
6.3.3. Sunflower .......................................................................................................................... 93
6.3.4. Wheat ................................................................................................................................ 94
7) CHAPTER 7 - CONCLUSIONS .................................................................. 96
8) CHAPTER 8 - FUTURE AGENDA ........................................................... 100
9) REFERENCES ............................................................................................. 101
10) APPENDIX ................................................................................................... 104
10.1. MONTE CARLO SIMULATION OUTPUTS........................................................................................104
viii

10.2. RISK MEASURES PER REGION ACROSS MODEL ..............................................................................132
10.2.1. Corn risk measures across regions and models: ............................................................ 132
10.2.2. Soybeans risk measures across regions and models: ..................................................... 133
10.2.3. Sunflower risk measures across regions and models: .................................................... 134
10.2.4. Wheat risk measures across regions and models: .......................................................... 135
10.3. RISK MEASURE RESULTS FOR SIMULATIONS WITH FITTED DISTRIBUTIONS AND WITH NORMALITY
ASSUMPTIONS ..................................................................................................................................................136
10.3.1. Corn Statistics ................................................................................................................ 136
10.3.2. Soybeans Statistics.......................................................................................................... 137
10.3.3. Sunflower Statistics ........................................................................................................ 138
10.3.4. Wheat Statistics .............................................................................................................. 140
10.4. EXTENDED DISCUSSION ...............................................................................................................142
10.4.1. Production, acreage and average yield in argentine agriculture ................................... 142
10.4.2. Tax Burden and transfer to Government ........................................................................ 145
10.5. TEST FOR SIGNIFICANT DIFFERENCES BETWEEN MEANS AND F-TEST FOR VARIANCES .................151
10.6. PROFIT FUNCTION INPUT VARIABLE’S PDFS AND CDFS ..............................................................155
ix

TABLE OF FIGURES
FIGURE 1-1. ARGENTINA PORTS AND PARANA UP RIVER. SOURCE:
HTTP://WWW.SHIPARRESTED.COM/CATEGORY/COUNTRIES/ARGENTINA., AND
HTTP://WWW.SSPYVN.GOV.AR/HIDROMETROS.HTML ....................................................................................... 3
FIGURE 2-1. MARKET EQUILIBRIUM IN A CLOSE ECONOMY. SOURCE: GARRIGA AND ROSALES, 2008. ................. 12
FIGURE 2-2. MARKET EQUILIBRIUM IN AN OPEN ECONOMY. SOURCE: GARRIGA AND ROSALES, 2008. ................. 13
FIGURE 2-3. EXPORT TAXES IN AN OPEN MARKET. SOURCE: GARRIGA AND ROSALES, 2008 ................................. 14
FIGURE 2-4. EVOLUTION OF SOWING AREA FOR THE MAIN FOUR CROPS IN BUENOS AIRES REGION. ..................... 17
FIGURE 3-1. ARGENTINE GROSS DOMESTIC PRODUCT IN BILLIONS OF U.S. DOLLARS. SOURCE:
WWW.TRADINGECONOMICS.COM, WORLD BANK GROUP. ............................................................................ 27
FIGURE 3-2. ARGENTINE PRIMARY SECTOR VALUE ADDED, ANNUAL FROM 1993 TO 2012. SOURCE: “INTEGRATED
AGRICULTURAL INFORMATION SYSTEM”, MINISTRY OF AGRICULTURE, CATTLE, AND FISHERIES”, SIIA-
MAGYP. ...................................................................................................................................................... 29
FIGURE 3-3. ARGENTINA PERCENTAGE UNEMPLOYMENT RATE (2002 – 2014). SOURCE:
WWW.TRADINGECONOMICS.COM / WORLD BANK GROUP, BASED ON DATA FROM INDEC (CENSUS AND
STATISTIC NATIONAL INSTITUTE). ................................................................................................................ 29
FIGURE 3-4. WORLD BANK PRICE INDEX. ANNUAL REAL US DOLLARS, 2005 (PINK SHEET). SOURCE: OWN
ELABORATION BASED ON WORLD BANK COMMODITY PRICE DATA (THE PINK SHEET). UPDATED ON
JANUARY ...................................................................................................................................................... 30
FIGURE 3-5. PRODUCTS EXPORTED BY ARGENTINA, FROM 1995 TO 2012, IN BILLIONS US DOLLARS. SOURCE:
OBSERVATORY OF ECONOMIC COMPLEXITY (OEC). HTTP://ATLAS.MEDIA.MIT.EDU/EXPLORE/
STACKED/HS/EXPORT/ARG/ALL/SHOW/1995.2012/. ...................................................................................... 30