ECN 212_ASU_ASSIGNMENT_2024_THE IMPACT OF SUGAR COMMODITY ECONOMIC POLICY ON THE WELFARE OF SUGAR PRODUCERS AND CONSUMERS

THE IMPACT OF SUGAR COMMODITY ECONOMIC POLICY ON

THE WELFARE OF SUGAR PRODUCERS AND CONSUMERS

I. INTRODUCTION

The agricultural sector is a provider of people's needs, both food and non-food. The

demand for agricultural products will continue to grow along with the increasing population.

This increasing population growth rate causes the demand for agricultural products to increase.

The demand for agricultural products is also increasing, especially for the nine basic food

products. The nine staples are rice/ sago/corn, sugar, vegetables and fruit, meat (beef and

chicken), cooking oil and margarine, milk, eggs, kerosene/LPG gas, and iodized and sodium

salt. One of the basic necessities needed by the community is sugar (Department of Industry

and Trade, 1998).

Sugar is a product of the agricultural sector in the plantation subsector. The plantation

subsector contributed 2.34 percent to Indonesia's GDP or IDR 55 518 billion (Statistics

Indonesia, 2013). Sugarcane is the basic raw material in the manufacture of sugar. In

Indonesia, sugarcane production in 2008 amounted to 2 668 428 tons and decreased in 2008.

2013 to 2 267 887 tons (Ministry of Agriculture, 2013). This decline in production prompted

the government to launch a sugar self-sufficiency program so that sugarcane and sugar

production can increase. The need for sugar for household and industrial consumption in

Indonesia is 5.8 million tons (Susianti, 2013). The government targets sugar self-sufficiency

in 2014 with an initial production of 5.7 million tons to 3.1 million tons. This production

value of 3.1 million tons can only meet household needs, not for industry. The decrease in the

self-sufficiency target is due to the lack of sugarcane plantation land and the revitalization of

sugar factories that are not running. The sugarcane plantation subsector requires an additional

350 000 ha of land and revitalization of 20 factories (Ministry of Agriculture, 2013).

Indonesia is both a sugar importer and exporter. Based on data from the Central

Bureau of Statistics (2013), the volume and value of Indonesia's sugar imports are greater

than Indonesia's sugar exports. The volume and value of sugar exports - imports can be seen

in Table 2.

Based on the data in Table 2, Indonesia is a net importer of sugar. The volume and

value of Indonesia's net sugar imports continue to increase. The increase in imports every year

has a major effect on sugar-related policies in Indonesia, especially in the production and

price sectors. The government has made several efforts to limit the entry of imported sugar,

one of which is import tariff barriers. The import tariff policy in Indonesia always changes

according to the conditions of the national economy, international trade, or regional

agreements. One of the regional agreements between countries that affect import tariff

policies in Indonesia is the ASEAN Economic Community (AEC).

The ASEAN Economic Community (AEC) is one of the policies that agree on ASEAN

as a single market and a single production base supported by the free flow of goods, services,

investment, educated labor, and capital flows. The AEC came into effect in 2015. All ASEAN

countries must liberalize trade in goods, services, investment, free skilled labor and freer

capital flows as outlined in the AEC Blueprint. The AEC is a more advanced and

comprehensive step from the ASEAN Free Trade Area (AFTA). The components of the free

trade flow of goods include a significant reduction and elimination of tariffs as well as the

elimination of non-tariff barriers under the AFTA scheme (Ministry of Trade, 2013).

Several ASEAN Member States, including Indonesia, have made reservations on

sensitive products. Indonesia made reservations on rice and sugar products as stated in the

Protocol to Provide Special Consideration on Rice and Sugar. The protocol regulates tariff

posts for rice and sugar. Rice and sugar products will be included in the Inclusion List in

2015. The Inclusion List are intra-ASEAN products where tariffs must be completely

eliminated (Ministry of Trade, 2013).

These economic conditions and the elimination of import tariffs from the ASEAN

Economic Community (AEC) regional agreement make the large supply of imported sugar in

the domestic market unavoidable. The large supply of imported sugarInadequate quantity and

timing led to an increase in sugar supply in the domestic market. This increase in sugar supply

causes the price of sugar to fall in the domestic market without being accompanied by a

decrease in production costs. Fixed production costs with falling prices cause sugarcane

farmers' revenues to decline and sometimes farmers even suffer losses. If the income of

sugarcane farmers continues to decline, there will be no incentive for farmers to increase

sugarcane production which causes sugar self-sufficiency to fail to be achieved and the

welfare of the community decreases. Therefore, it is important to conduct research on the

impact of sugar commodity economic policy on the welfare of sugar producers and consumers

in Indonesia.

1.1. Problem Research

The development of sugarcane production in Indonesia over the past few years has

continued to decline. Based on data in Table 3, in 2010 sugarcane production (sugar

equivalent) reached 2.29 million tons and fell 1.95 percent in 2011 to 2.24 million tons. Sugar

production in the 2013 milling season also decreased by 10-20 percent compared to 2012. In

the 2013 milling season, sugar production ranged from 2.3 million tons while sugar

production in the 2012 milling season reached 2.6 million tons (Ministry of Agriculture,

2013).

The decline in production was caused by anomalous weather conditions, especially the

long rainy season in a number of sugar factory areas in Indonesia. The decline in national

sugar production is also caused by the shrinkage of land for sugarcane plantations, sugar

factories that are unable to work optimally, the lack of capital support for sugarcane farming

and the sugar industry, sugar import policies, and sugarcane farming that can no longer lift the

welfare of the peasants (Admin, 2013) Indonesia's sugar production is mostly consumed

domestically and only a small portion is exported to foreign countries. The low national sugar

production which continues to decline every year causes domestic sugar consumption cannot

be met by domestic production. The development of sugar production and consumption in

Indonesia is presented in Table 4.

Based on the data in Table 4, sugar consumption in Indonesia tends to be higher than

sugar production each year. The shortage of domestic sugar supply requires Indonesia to

import sugar from various countries. The development of Indonesia's sugar imports over the

period of recent years has a pattern that tends to increase while Indonesia's sugar exports have

a pattern that tends to decrease even though it had increased in 2011 as shown in Table 2. In

order to meet domestic sugar consumption needs, the Government has made various efforts

through several policies such as the sugar self-sufficiency policy by increasing national

production, but in decision making and implementation, Indonesia's policies are also

influenced by various international policies that affect Indonesia's sugar imports.

The ASEAN Economic Community (AEC) is one of the regional agreements between

ASEAN countries that supports the elimination of import tariffs. The policy of import tariff

elimination began on January 1, 2015 in a progressive manner. The progressive elimination of

import tariffs is a decrease in tariffs to 10 percent, a decrease in tariffs to 5 percent, and the

elimination of import tariffs to zero percent. This import tariff elimination policy will lead to

an increase in sugar imports so that sugarcane farmers and the domestic sugar industry have

the potential to suffer losses. The entry of imported sugar into Indonesia causes national sugar

to lose part of its market. The increased supply of imported sugar and the decline in the

national sugar market is resulting in falling prices. Many sugarcane farmers left their

profession due to low sugar prices. This condition causes farmers to experience losses which

have an impact on the decline in farmer welfare (Toharisman, 2013).

Economic policy on sugar commodities in the form of an increase in sugar prices at

the farm level by 30 percent and an increase in sugar stocks by 20 percent is expected to be

able to improve the welfare of farmers and society as a whole due to the reduction in import

tariffs that will be applied. In connection with this description, the following research

problems can be formulated:

1. Factors affecting the supply, demand and price of sugar.

2. The impact of sugar commodity economic policies on sugar supply, demand, and price.

3. The impact of sugar commodity economic policy on the welfare of sugar producers and

consumers in Indonesia.

1.1. Characteristics Sugar

The most widely traded cane sugar is known locally as raw sugar, white crystal sugar,

and refined crystal sugar. These types of sugar have names that are not always the same in

international trade. The international name for raw sugar is raw sugar, white crystal sugar is

plantation white sugar or mill white sugar, and refined crystal sugar is white sugar. Therefore,

white sugar is the same as refined crystal sugar and not white crystal sugar (Agrirafinasi,

2013).

Raw sugar or raw sugar is made from sugarcane sap which is processed simply by

filtering out solids or mud and then crystallized. The sugar is dark brown in color because it

still contains residual impurities and molasses (molasses) so it is not suitable for consumption.

White crystal sugar or plantation white sugar is made from sugarcane sap that is processed

with longer stages than the process of making raw sugar. After filtering out the impurities, the

cane juice is cleaned through a carbonation or sulfitation process. The cleaner cane juice is

thickened and then crystallized into white crystal sugar. The color of the sugar becomes white

but slightly cloudy. Some factories use a double carbonation process to obtain a whiter sugar

color. The sulfitation process is also no longer used because it is unhygienic due to the

residual sulfur left in the sugar. Refined crystal sugar or white sugar is the whitest in color due

to the following reasons: (1) the raw material is raw sugar, (2) the manufacturing process

includes carbonation and also uses ion-exchange technology. This ion-exchange process is

able to separate non-sucrose molecules such as residual impurities, mineral residues, and

color molecules that are missed in the carbonation process so that the result is very white

crystal sugar (Agrirafinasi, 2013).

Raw sugar is used by refined sugar factories, cane-based sugar factories, and MSG

(flavoring) factories. White crystal sugar is used for direct public consumption, and refined

crystal sugar is used by the food industry, beverages, and pharmaceuticals (Nusantara Sugar

Club, 2014). The volume and quality of sugar basically depends on two main factors, namely

the sugar content in sugar cane stalks and the processing of sugar cane juice into crystal sugar.

If the sugar content is maximized and the processing in the factory is efficient, the results will

be maximized. The process of producing crystal sugar in sugar factories is to separate sugar or

sucrose from sugar cane stalks and process it into crystal sugar granules. Damage and leakage

of sucrose in the process needs to be minimized so that the sucrose that can be crystallized is

maximized. Pure sucrose is crystals that do not contain water (anhydrous), non-uniform

square shape (monoclinic), odorless, and brilliant white with a sweet taste and specific gravity

of 1.58 at a temperature of 150o C. The level of whiteness of sugar color is seen through the

ICUMSA (International Commission for Uniform Methods of Sugar Analysis) standard. The

whiter the sugar, the smaller the ICUMSA value and the darker the color, the higher the

ICUMSA value. The unit of ICUMSA value is the international scale unit (IU). The lowest

raw crystal sugar has an ICUMSA value of 1200 IU, white crystal sugar 150-90 IU, and

refined crystal sugar as high as 45 IU (Agrirafinasi, 2013).

1.2. ASEAN Economic Community (AEC) Regional Agreement

In 1997, the ASEAN Heads of State agreed on the ASEAN Vision 2020, which is to

create a stable, prosperous, and highly competitive region with equitable economic

development characterized by a reduction in poverty levels and socio-economic disparities

(ASEAN Summit, 1997). Then in 2003, 3 (three) pillars were agreed upon to realize ASEAN

Vision 2020 which was accelerated to 2015, namely: (1) ASEAN Economic Community, (2)

ASEAN Political-Security Community, (3) ASEAN Socio-Cultural Community (ASEAN

Summit, 2003).

In 2004, ASEAN began to cooperate with countries outside ASEAN in the economic

field. The first cooperation was with China (ASEAN-China Free Trade Area) in the goods

sector. In 2005, ASEAN economic integration was further enhanced by adding priority

sectors in 2010 and logistics services in 2013. In 2007, The Heads of State agreed to

accelerate the achievement of the AEC from 2020 to 2015. In 2007, the ASEAN Charter and

AEC Blueprint were signed. In 2009, the ASEAN Trade in Goods Agreement (ATIGA) was

signed. The decision to accelerate the establishment of the AEC to 2015 was made in order to

strengthen ASEAN's competitiveness in the face of global competition such as with India and

China. Some other considerations underlying the acceleration of the AEC are: a) a potential

reduction in production costs in ASEAN by 10-20 percent for consumer goods as a result of

economic integration; and b) improving regional capabilities with the implementation of

international standards and practices and competition (Ministry of Trade, 2013).

The AEC Blueprint is a guideline for ASEAN member countries to achieve AEC

2015, where each country is obliged to implement the commitments in the blueprint. The

AEC Blueprint contains four main frameworks (The ASEAN Secretariat, 2013):

1. ASEAN as a single market and international production base with elements of free flow of

goods, services, investment, educated labor, and freer flow of capital.

2. ASEAN as a region with high economic competitiveness with elements of competition

regulation, consumer protection, intellectual property rights, infrastructure development,

taxation, and e-commerce.

3. ASEAN as a region with equitable economic development with elements of small and

medium enterprise development, and ASEAN integration initiatives for CMLV countries

(Cambodia, Myanmar, Laos, and Vietnam).

4. ASEAN as a region is fully integrated into the global economy with elements of a coherent

approach to economic relations outside the region and enhanced participation in global

production networks.

The ASEAN Trade in Goods Agreement (ATIGA) is a modification of the overall

ASEAN agreement on liberalization and facilitation of trade in goods. The ATIGA is a

refinement of the ASEAN agreement in trade in goods in a comprehensive and integrative

manner in accordance with the ASEAN Economic Community (AEC) Blueprint agreement

related to the free flow of goods as one of the elements forming a single market and regional

production base. ATIGA covers general principles of international trade (non-discrimination,

Most Favoured Nations-MFN treatment, national treatment), tariff liberalization, non-tariff

arrangements, rules of origin, trade facilitation, customs, standards, technical regulations and

adjustment inspection procedures, SPS (Sanitary and Phytosanitary Measures), and trade

remedy policies (safeguards, anti-dumping, countervailing measures) (Ministry of Trade,

2013).

ATIGA has major commitments in tariff reduction and elimination. The elimination of

tariffs on all intra-ASEAN products, except those in the Sensitive List (SL) and Highly

Sensitive List (HSL) categories, will be carried out according to the schedule and

commitments set out in the CEPT- AFTA agreement. Products in the SL and HSL categories

must enter the Inclusion List scheme in accordance with the agreed schedule. Once included

in the Inclusion List scheme, tariffs on these products will be reduced to 0-5 percent. Rice and

sugar products will be included in the inclusion list in 2015 in accordance with the provisions

in the Protocol to Provide Special Consideration on Rice and Sugar (Government of ASEAN,

2007).

1.3. Trade Policy Sugar

To overcome international trade problems, trade liberalization has been agreed upon in

the Uruguay Round (PU) as a series of the General Agreement on Tariff and Trade (GATT)

on December 15, 1993. Efforts to reduce sugar trade distortions have been taken by various

countries by realizing commitments on four important things, namely:

1. Sanitary/phytosanitary measures (aflatoxin contamination and strict standards).

2. Domestic assistance/support as measured by the total aggregate measurement of support

(AMS) where developed countries reduce 20 percent, while developing countries 13

percent.

3. Market access is tariffication, a reduction in tariffs commonly applied by various

countries (ad valorem tariffs) which developed countries are expected to realize in 2000

with a reduction of 21 to 23 percent, while developing countries in 2004 by 9 to 14

percent and specific tariffs whose proportion of application is very limited ranging from

24 to 26 percent.

4. The reduction in export subsidies is based on a decrease in export volume, the subsidized

volume being 18 percent of agricultural products marketed in the world and the value of

exports.

However, the implementation of the GATT agreement has not touched much on sugar trade

distortions (Susila and Sinaga, 2005). This is because (Wahyuni et al, 2009):

1. Sugar has little effect on health and the environment.

2. Various facts about the subsidy policies adopted by various countries still place the sugar

industry at the receiving end of large subsidies.

In the framework of the GATT agreement, the Indonesian government opened the import

market dramatically. In order to increase economic efficiency, the government issued Minister

of Trade Decree No.25/MPP/Kep/1/1998 which no longer gave Bulog a monopoly to

i m p o r t strategic commodities, including sugar (Susila and Sinaga, 2005).

The Indonesian government's decision to revoke BULOG's monopoly o n sugar

procurement and implement a zero percent tariff on sugar imports has put the local sugar

industry at risk as imported sugar is cheaper than domestic sugar. This showed the

inefficiency of the sugar industry in Indonesia and many domestic sugar factories were

threatened with bankruptcy because they could not compete with imported sugar. Through the

Decree of the Minister of Finance No. 568/KMK.01/1999, which came into effect on January

1, 2000, all importers, both general importers (IU) and producer importers (IP), including

BULOG, were allowed to import sugar with the provision of import duty of 20 percent for

raw sugar and 25 percent for white crystal sugar. In 2004, in order to support the acceleration

program, the government made improvements to the previous policy by issuing a Decree of

the Minister of Industry and Industry Trade No. 527/MPP/Kep/9/2004 where the government

re-involved SOEs such as BULOG and PT Perusahaan Perdagangan Indonesia in sugar

trading in Indonesia. BULOG has a role as the sole distributor to market sugar owned by

PTPN and PT Rajawali Nusantara Indonesia (RNI) through its network spread throughout

Indonesia (Rahman, 2013).

When Indonesia's economic crisis began to ease in 1999, domestic sugar prices

actually experienced a significant decline. The decline was due to three factors: the world

sugar price continued to decline, the rupiah exchange rate strengthened, and the absence of

import tariffs (Wahyuni et al, 2009). This puts pressure on domestic sugar prices. To protect

producers, the government set the provenue price of sugar. The provenue price policy turned

out to be an ineffective policy because it was not supported by an adequate follow-up plan

such as funding for policy implementation. Setting the provenue price too low can kill the

sugar industry because it will have difficulty obtaining raw materials. Conversely, setting the

price too high will grow the sugar industry but increase the subsidy that must be provided by

the government (Malian, 2004). Prior to 2000, the price of sugar received by farmers was the

provenue price, which was the purchase price of BULOG to sugarcane farmers. From 2000-

2003, the price of sugar received by farmers was the auction price agreed between farmers

and sugar investors, while after 2004 until now the price of sugar received by farmers is the

auction price based on the cost of goods sold (HPP) as the basic price of sugar purchases by

investors. The government issued a policy of setting the cost of goods sold (HPP) in the sugar

industry to provide protection to farmers. This sugar HPP is one of the incentives for farmers

in sugarcane cultivation. The cost of goods sold is set by the government and revised annually

(Rahman, 2013).

The government also launched a special National Sugar Self-Sufficiency program

related to controlling sugar imports. Self-sufficiency is considered important because sugar

prices are predicted to continue to rise. The government seeks to increase production and

productivity through accelerated programs and improved sugar trading and import policies. In

order to realize sugar self-sufficiency, a refined sugar factory was developed to help meet the

sugar needs of the food and beverage industry. Refined sugar factories obtain facilities in

importing raw sugar raw materials, namely by waiving import duties or import taxes. The

same provisions regarding import duty relief also apply to the refined sugar industry that is

expanding its business. In order to protect the price of domestic white crystal sugar, the trade

of refined sugar is regulated by Minister of Trade Decree No.527/MPP/Kep/9/2004 that

refined sugar is only for raw material needs for user industries and the distribution of refined

sugar directly to user industries without going through distributors. In the letter of the

Minister of Trade No.111/2009, it is stated that in meeting the needs of refined sugar for the

user industry or the food and beverage industry, each refined sugar producer can officially

appoint a distributor, then the distributor can officially appoint a subdistributor. distributors

who do not have a letter of appointment or appointment from refined sugar producers are

prohibited from distributing or trading refined sugar. The same applies to subdistributors

(Wahyuni et al, 2009).

1.4. Previous Research

Some studies that can be used as references include research by Rahman (2013);

Subekti and Carolina (2011); Arsyad, Sinaga, and Yusuf (2011); Hadi and Mardianto (2004);

and Fitriana (2012). The results of these studies can be seen in Table 4.

2.3.1. Research on Sugar

Research on sugar has been conducted by many previous researchers such as research

by Rahman (2013) and Subekti and Carolina (2011). Rahman's research (2013) analyzed the

prospects of Indonesia's sugar trade in the implementation of the ASEAN-China free trade

agreement framework. Subekti and Carolina's (2011) research analyzed the effect of sugar

import tariff policy on the integration of domestic and world sugar markets (Table 4).

2.3.2. Research on Agricultural Commodity Trade Policy

Previous research on agricultural commodity trade has also been conducted by Arsyad,

Sinaga, and Yusuf (2011) and Hadi and Mardianto (2004). These studies looked at the impact

of a trade policy (export or import) on the factors that influence it by using two different

analytical tools. Arsyad, Sinaga, and Yusuf (2011) used a simultaneous equation model with

the Two-Stages Least Squares estimation method while Hadi and Mardianto (2004) used the

Constant Market Share approach model (Table 4).

2.3.3. Research on the Effect of Policies on Welfare

Fitriana (2012) examines the effect of policies on community welfare. The study

examines the impact of policy changes that will affect the amount of community welfare. The

welfare indicators used in the study were changes in producer surplus and consumer surplus

(Table 4).

1.5. Novelty Research

This study has similarities and novelty compared to the research of Subekti and

Carolina (2011) and Rahman (2013). The similarity of this study with Subekti and Carolina

(2011) is to analyze the effect of sugar import tariff policy on the domestic sugar market. The

difference is that the research conducted by Subekti and Carolina (2011) uses the Vector

Autoregressive (VAR) and Vector Error Correction (VEC) models while this study uses a

simultaneous equation model with the Two- Stages Least Squares estimation method.

The similarity of this research with Rahman's (2013) research is to analyze the impact

of policies on the welfare of sugar producers and consumers in Indonesia, while the difference

is that this research is more focused on discussing the impact of reducing and eliminating

sugar import tariffs due to the ASEAN Economic Community (AEC) regional agreement.

1.1. Framework Theoretical

The main components of sugar trade in Indonesia include production, consumption

and import activities. The theory of production and supply functions, demand functions,

prices, international trade theory, import demand, producer surplus and consumer surplus, and

the impact of tariffs on welfare are presented.

1.1.1. Production and Supply Functions

Production is the process of converting inputs into outputs thereby creating added

value for a good or commodity. The production function relates to the relationship between

the inputs used in the production process and the quantity of output produced (Lipsey, et al.,

1987). Demand Function

Demand is the amount of goods purchased or demanded at a certain price and time.

Demand is related to consumers' desire for goods and services to be fulfilled. The demand

function states that the quantity demanded depends on price, income, and preferences

(Nicholson, 2002). According to Koutsoyiannis (1979), the demand function is derived as

follows of the maximized consumer utility function with a certain income level constraint.

Price

Price is the amount of money that must be spent to obtain one unit of a commodity.

Economic theory states that the price of a good or service in a competitive market is

determined by market demand and supply. Supply relates to producers while demand relates

to consumers. The price formed and agreed upon by producers and consumers is the market

price. At this price level, the amount of goods offered is equal to the amount of goods

demanded. The market price is also called the equilibrium price.

Market prices have two main functions, namely as (Nicholson, 2002):

1. Signaling/informing producers on how many goods should be produced to achieve

maximum profit.

2. Determines the level of demand for consumers who want maximum satisfaction.

An increase in demand causes the equilibrium price to increase so demand affects price

positively. Supply affects prices negatively, where if there is an increase in supply, prices

will tend to fall. This price reduction is caused by the quantity of goods offered by

producers being greater than what is needed or desired by consumers (Fitriana, 2012).

Price formation in food/agricultural commodities is more influenced by supply

because demand tends to stabilize following the development trend. Factors affecting the

supply of food/agricultural commodities are production/harvest factors and storage behavior

(Tomek, 2000). Price variations are large during the planting season and smaller during the

harvest season.

while storage technology for perishable products will reduce the pressure of price fluctuations

of such commodities.

1.1.2. International Trade Theory

International trade is trade carried out by residents of a country with residents of other

countries by mutual agreement. The people in question can be individuals (individuals with

individuals), between individuals and the government of a country, or the government of a

country with the government of another country. International trade is one of the factors to

increase GDP. International trade will encourage industrialization, transportation

advancement, globalization, and the presence of multinational companies. International trade

allows a country to consume more goods than would be available along the production

possibility frontier in a state of self-sufficiency without foreign trade (Lindert and

Kindleberger, 1993).

According to Lipsey, et al. (1987) international trade provides two sources of benefits

for countries that trade. These sources of benefits are:

1. The differences in climate and natural resources that each country in the world has

resulted in advantages in producing certain goods and weaknesses in producing other

goods.

2. The decrease in production costs in each country is due to the increase in the scale of

production due to specialization.

International trade allows each country to specify production and certain goods so as

to achieve a high level of efficiency with a large scale of production. The difference in

resources owned by each country causes the country to try to produce products at a relatively

low cost. The difference in resources is what causes price differences and determines a

country's decision to export and import (Rahman, 2013).

1.1.3. Inquiry Import

Import is a trade activity where a country buys goods from abroad. Import demand

occurs due to several factors including (Purwanto, 2002):

1. Domestic production of goods is insufficient for consumption needs.

2. These goods are essential to life but the country cannot produce them properly due to

technological and climatic limitations.

3. A country has the technology but not the raw materials (in which case it will re-export).

Import demand is the excess of domestic demand in the importing country (excess

demand). According to Lindert and Kindleberger (1993) the import demand curve by a

country in the world market is the difference between the demand and supply of the

commodity in question in that country. Sugar import demand can be formulated as follows:

Mt = Qd - Qg ................................................................................................................(3.22)

where :

Mt= Sugar import (Ton)

Qd= Sugar demand (tons) Qg= Sugar production (tons)

1.1.4. Producer Surplus and Consumer Surplus

International trade policies such as the imposition of tariffs and import quotas for

importing countries or export subsidies for exporting countries are policies carried out by the

government in protecting domestic producers and consumers. The impact of these policies can

be known by using the welfare economic theory approach, namely the concept of measuring

economic surplus. According to Fauzi (2010) the concept of surplus places a monetary value

on the welfare of the community from extracting and consuming resources. Surplus is also an

economic benefit that is nothing but the difference between gross benefits and costs incurred

to extract resources.

Economic surplus can be divided into consumer surplus and producer surplus.

Consumer surplus can be defined as the difference between the maximum amount of money

consumers are willing to pay and the value actually paid for a certain amount of a product.

Producer surplus is the difference between the amount of money value actually received by

the producer and the minimum amount of value desired by the producer (Just, et al., 1982).

Producer Surplus and Consumer Surplus under Market Equilibrium Conditions

If it is assumed that there is no trade abroad, then in the equilibrium state (Pe and Qe),

the producer surplus is P1EPe and the consumer surplus is P2EPe. The weakness of measuring

consumer surplus with an ordinary demand curve is that it does not consider the income effect

due to price changes, so the concept of consumer surplus does not reflect the condition of

consumers' willingness to pay or receive. Tariff Impact on Welfare

Tariffs are taxes designed to increase the price of foreign goods (Lipsey, et al., 1987).

The purpose of imposing tariffs is to control the price of a product and limit the number of

incoming products so that domestic products are not less competitive with imported products

even though international trade continues. According to Lindert and Kindleberger (1993), the

imposition of tariffs almost always reduces world welfare even though it will help groups

related to the production of import substitution goods. Tariffs will be important if Indonesia as

2 1 2

a sugar importing country conducts trade relations with other countries.

Figure 3: Impact of Import Tariffs

Figure 3 shows the sugar market in Indonesia, which is assumed to be a small country.

The domestic price would be equal to the world price if free trade were possible. The

implementation of tariffs causes the domestic sugar price to be higher than the world price

and the excess is the amount of tariff imposed. The consumer-level price of sugar in Indonesia

with tariffs is equal to the world price plus the tariff to the domestic market so that domestic

sellers benefit while consumers lose.

This price change affects the behavior of sugar sellers and consumers in the domestic

market. The tariff causes the domestic supply quantity to rise from Qs to Qs while the

domestic demand quantity falls from Qd to Qd . The implementation of tariffs reduces the

quantity of imports and pushes the domestic market closer to the no-trade equilibrium

condition. The welfare changes due to the tariff policy can be seen in Table 5.

Based on Table 5, it can be seen that the imposition of tariffs on consumers will reduce

welfare by (C+D+E+F). This loss of consumer welfare is transferred to producer surplus and

government revenue. Producers receive a welfare transfer of (C) so that the imposition of

tariffs increases producer welfare. The welfare transferred into government revenue is (E) but

there is a lost surplus that is not owned by anyone amounting to (D+F) so in general the

imposition of tariffs will reduce total welfare.

1.2. Framework Operational

Research on the impact of the ASEAN Economic Community (AEC) regional

agreement on Indonesia's sugar imports is based on the understanding that sugar is a major

commodity in fulfilling people's needs and is classified as one of the nine basic ingredients

(SEMBAKO). Sugar trade has broad market opportunities due to high consumption from

households and industries in both domestic and world markets.

The operational framework chart in Figure 4 illustrates that sugar demand continues

over time while national sugar production is relatively low so that it has not been able to meet

sugar demand nationwide. In order to maintain the availability of domestic sugar stocks, it is

necessary to import. The application of import tariffs on sugar commodities continues to

change from year to year in accordance with national economic conditions, international

trade, or regional agreements. The ASEAN Economic Community (AEC) is one of the regional

agreements that supports progressive tariff reduction and elimination of sugar import tariffs in

the ASEAN trade market. This reduction and planned elimination of tariffs has led to high

sugar imports that impact domestic prices and public welfare.

4.1. Types and Sources Data

The type of data used in this research is secondary data in the form of annual time

series with a research time span of 1990 to 2012. The data in this study were obtained from

agencies related to the theme of this thesis writing such as the Ministry of Trade of the

Republic of Indonesia (Kemendag RI), the Ministry of Agriculture of the Republic of

Indonesia (Kementan RI), the Indonesian Sugar Council (DGI), the Nusantara Sugar Club

(NSC), and the Central Statistics Agency (BPS). In addition, this research will also be

supported by several data reference materials for completeness and data adjustment. The

required reference materials are obtained from Bogor Agricultural University (IPB), Center

for Socio-Economic and Agricultural Policy (PSEKP), Food Agricultural Organization

(FAO), and World Bank (WB).

4.2. Specifications Model

A model is an abstraction or simplification of phenomena that exist in the real world.

One of the quantitative approach models that are often used for analyzing economic problems

is the econometric model (Hallam, 1990). According to Koutsoyiannis (1977) in building

econometric models there are four main stages that must be passed, namely model

specification, model estimation, model validation, and model application. A good model must

be able to meet economic criteria and statistical criteria which are seen from a degree of

accuracy (goodness of fit) usually by looking at statistically significant R2 and econometric

criteria, namely whether a model estimation has unbiased properties, consistency, adequacy,

and efficiency.

One of the most important things to note is the specification stage of the model which

is expected to be truly close to the real phenomenon. Based on a review of the development of

sugar trade, relevance to previous research, and theoretical framework, the Indonesian Sugar

Trade Model is specified in the form of simultaneous equations whose interrelationships

between variables are presented in Figure 5.

4.2.1. Area Sugarcane

The response analysis of sugarcane plantation area is differentiated based on the status

of the concession, namely smallholder plantations, large state plantations, and large private

plantations. Sugarcane area is influenced by the price of sugar where in this study a

distinction is made on the price of sugar that affects smallholder plantation companies with

large state and private plantation companies. Smallholder plantations are influenced by the

price of sugar at the farm level, large state plantations are influenced by the price of sugar at

the level of large traders in the previous year, and large private plantations are influenced by

changes in sugar prices at the consumer level. Sugarcane farming in increasing its area pays

attention to fertilization, pest control, and the use of superior seeds. This study only uses urea

fertilizer because data on the price of KCL fertilizer, ZA fertilizer, and the price of manure are

not available. The use of other inputs such as pesticides and seeds are also not included in the

equation because data is not available. Other factors affecting sugarcane plantation area are

the real price of grain at the farm level as a competitive output of sugarcane, real credit

interest rates, real wages of plantation sector labor, production capacity of sugar factories, and

the previous year's sugarcane plantation area. Sugar Productivity

Sugar productivity is used in the form of hablur sugar, which is one of the products of

sugarcane sap processing in addition to molasses (molasses) and blotong (sap sediment). The

productivity of sugar cane is differentiated based on the status of the business, namely the

productivity of sugar cane of smallholder plantations, the productivity of sugar cane of large

state plantations, and the productivity of sugar cane of large private plantations. The

productivity of sugar cane is influenced by the area of sugar cane plantations, Indonesian

rainfall, Indonesian sugar cane yield, and time trends,

4.3. Model Estimation Method

Data processing in this study was conducted using Microsoft Excel 2007 computer

program and Statistical Analysis Software/Econometric Time Series (SAS/ETS) version 9.3

for Windows with SYSLIN procedure for estimation and SIMNLIN procedure for model

simulation (Sitepu and Sinaga, 2006). Model identification led to the conclusion that the

model was overidentified. This result allows the equation to be estimated by Two-Stages Least

Squares (2SLS), Three-Stages Least Squares (3SLS), Limited Information Maximum

Likelihood (LIML), or Full Information Maximum Likelihood (FIML) methods. The method

that will be used in this research is Two-Stages Least Squares (2SLS).

According to Koutsoyiannis (1977), some reasons for using this 2SLS method are:

1. This method is more suitable when the number of samples is small.

2. This method avoids biased and inconsistent estimates.

3. This method is one of the suitable methods to be used in parameter estimation of simultaneous

econometric models, especially for simultaneous equations.

4. This method is more efficient when not all equations in the system will have their parameters

estimated.

The estimation method is used to estimate the parameters of sugar acreage,

productivity, demand, import, and price. Furthermore, the model simulation is useful for

analyzing the impact of sugar commodity economic policy on the welfare of the Indonesian

people.

4.4.1. Model Fit Test (F Test)

The F statistical test basically shows whether all explanatory variables included in the

model have a joint influence on endogenous variables. The null hypothesis (H0) to be tested is

whether all explanatory variables included in the model have a joint influence on the

endogenous variable. parameter in the model is equal to zero and the alternative hypothesis

(H1) is that at least one parameter is not equal to zero.

4.4.2. Partial Significance Test (t test)

The t statistical test basically shows how far the influence of one explanatory variable

individually in explaining the variation in endogenous variables. The null hypothesis (H0) to

be tested is whether a parameter (βi) is equal to zero and the alternative hypothesis (H1) is

whether a parameter (βi) is not equal to zero.

4.4.3. Autocorrelation Test

Autocorrelation is a deviation in classical linear assumptions where there is a

correlation between the errors of the i-th observation and the j-th observation. Autocorrelation

occurs in time series data. Autocorrelation will As a result, the estimated regression coefficients

are still linear and still unbiased, but the variance of the estimated regression coefficients has a greater

variance than the variance of the estimated regression coefficients in a model that does not have

autocorrelation (Putri, 2013). In order to determine whether or not there is an autocorrelation problem

in each equation, it is necessary to conduct an autocorrelation test using the DW statistic (Durbin-

Watson statistic).

If the model contains simultaneous equations and lag variables, then to determine

whether or not there is autocorrelation in the equation, the durbin-h statistic is used. The

durbin-h value is obtained from the following calculation (Pindyck and Rubinfeld, 1998):

4.4.4. Multicollinearity Test

Multicollinearity is a perfect linear relationship between independent variables in the

model. Multicollinearity arises if two or more independent variables (or a combination of

variables) are highly correlated with each other. If there is a correlation between two

independent variables, the parameter conjecture

coefficients can still be obtained but their interpretation becomes difficult. The existence of

multicollinearity implies that there are very few data where the values of other independent

variables are the same. When changes occur in an independent variable that experiences

multicollinearity, the observations of other independent variables in pairs are likely to change

as well in the direction of the collinearity (Juanda, 2009).

One way to determine multicollinearity problems can be seen from the Variance

Inflation Factor (VIF) value. VIF is a way to detect multicollinearity by looking at the extent

to which an explanatory variable can be explained by all the other explanatory variables in the

regression equation. A high VIF indicates that multicollinearity has increased the variance of

the estimated coefficients and consequently decreased the value of t. The higher the VIF

value, the more severe the impact of multicollinearity. In general, serious multicollinearity

problems occur when the VIF value of a variable is greater than 10 (Sarwoko, 2005).

4.4.5. Heteroscedasticity Test

One of the important assumptions of the least squares method estimation is that the

residual variance is constant or the variance of the residuals is homogeneous. This assumption

is called homoscedasticity. If the variance of the residuals is not the same or the variance of

the residuals is not constant for each observation of the independent variables in the model,

then there is a heteroscedasticity problem. If all the classical assumptions in a linear

regression model are met, except the heteroscedasticity problem, then the result is: a) the

estimated regression coefficient parameters remain unbiased and consistent, but the standard

error is biased downward; and b) the OLS estimator is no longer efficient (Juanda, 2009).

4.4. Policy Model Simulation

Historical policy simulations in the period 2003-2012 were carried out with the aim of

seeing and knowing the impact of sugar commodity economic policies and import tariff

policies on supply, demand, prices, producer welfare, and consumer welfare of Indonesian

sugar. Sugar is one of the sensitive products for Indonesia. Indonesia has a reservation on

sugar products as stated in the Protocol to Provide Special Consideration on Rice and Sugar.

Sugar products will be included in the Inclusion List in 2015 so that the policy simulation

scenario carried out in this study is:

1. Implementation of a policy to reduce sugar import tariffs to 10 percent. This policy alternative

is based on the plan to apply sugar import tariffs according to the end rate of the Protocol to

Provide Special Consideration on Rice and Sugar.

2. Implementation of a policy to reduce sugar import tariffs to 5 percent. This policy alternative

is based on the plan to apply sugar import tariffs according to the end rate of the Protocol to

Provide Special Consideration on Rice and Sugar.

3. Elimination of sugar import tariffs to zero percent. This policy alternative is based on the plan

to implement sugar import tariffs in accordance with the main commitments of ATIGA

(ASEAN Trade in Goods Agreement) at the final stage.

4. A 30 percent increase in sugar prices at the farm level. This policy alternative is based on

APTRI (Association of Sugar Cane Farmers)which wants a 30 percent increase in the sugar

price ceiling. The existing price ceiling that takes into account 10 percent of the profit from

the cost of production for farmers is too small because farmers need one year to get 10 percent

profit.

5. A 20 percent increase in sugar stocks. This policy alternative is based on the discourse of the

DPR Working Committee on Sugar Self-Sufficiency to make Perum BULOG the buffer stock

for sugar price control.

6. A combination of reducing sugar import tariffs to 10 percent and increasing sugar stocks by

20 percent. This policy alternative is carried out to see the effectiveness of economic policy

on sugar commodities in protecting sugar consumers in Indonesia.

7. A combination of eliminating sugar import tariffs to zero percent and increasing sugar prices

at the farm level by 30 percent. This policy alternative is carried out to see the effectiveness of

economic policies on sugar commodities in protecting sugar producers in Indonesia.

Development of Sugar Production in Indonesia

Sugarcane is a crop grown for sugar raw materials. The purpose of planting sugar cane

is to produce high yields of sugar. Hablur is crystallized sucrose, where in the sugar

production system the formation of sugar occurs in the metabolic process of plants. The sugar

factory only functions as an extraction tool to extract nira from the sugar cane stem and

process it into crystal sugar (Rahman, 2013). Sugar is only produced in nine provinces in

Indonesia. The growth of sugar production is not significantly able to reduce dependence on

sugar imports. The increase in sugar prices, which annually averages 11.38 percent, has not

been able to increase sugarcane cultivation. The development of sugarcane plants in Indonesia

until 2011 has reached 434 962 hectares with the production of 2 244 154 tons of refined

sugar spread across 9 provinces and in 2012 increased to 453 421 hectares with the production

of 2 600 352 tons of refined sugar (Billah, 2013).

The nine provinces in Indonesia that produce national hablur sugar are North Sumatra,

South Sumatra, Lampung, West Java, Central Java, Yogyakarta, East Java, South Sulawesi

and Gorontalo. Hablur sugar production for each province can be seen in Table 8.

Based on the average data of sugar production in Indonesia for the last three years

(2010-2012), East Java is the province with the largest contribution to Indonesia's total sugar

production, which is 47.57 percent. This is because East Java is the province with the largest

sugarcane plantation area in Indonesia. Based on data from the Central Bureau of Statistics

(2013), in 2012 the area of sugarcane plantations in East Java Province amounted to

44.72 percent of the total area of sugarcane plantations in Indonesia. Lampung Province is a

production center in the Sumatra region with a contribution to national sugar production of

30.25 percent and ranks second nationally. The area of sugarcane plantations in Lampung

province is 25 percent of the total area of sugarcane plantations in Indonesia (Badan Pusat

Statistik, 2013).

In the 2013 milling season, the performance of the national sugar industry from 62

sugarcane-based sugar factories was cumulatively recorded as follows: 469 228.2 Ha felled

area, 35 526 070 tons of sugarcane production, 7.18 percent yield, and 2 551 024 tons of

refined sugar production. Cumulative monthly performance developments from January to

December 2013 are presented in Table 9.

In Table 9, the performance of the sugar industry each month is cumulative from the

previous month. Based on Nusantara Sugar Club (2014) data, at the end of December 2013,

the sugarcane area cut down was 469 228 hectares, with 298 254 hectares (63.56 percent)

belonging to SOEs and the remaining 170 975 hectares (36.44 percent) belonging to BUMS.

Sugar production produced was 2 551 024 tons with details of 1 538 432 tons (60.30 percent)

owned by BUMN and the remaining 1 012 592 tons (39.70 percent) owned by BUMS. Based

on the national sugar industry, an overview of the performance of the sugar industry made

from sugarcane raw materials in the last five years can be seen in Table 10.

Table 10 shows that the yield value is very important in producing sugar. In 2012,

sugarcane production was lower than in 2013, but with a yield of 8.13 percent, it produced

higher refined sugar. Based on the Nusantara Sugar Club study (2014), if the 2013 national

yield can be increased by 1 percent to 8.18 percent, sugar production will reach 2.90 million

tons or an increase of 345 000 tons or the equivalent of the output of 3 (three) sugar factories

with a capacity of 10 000 TCD.

Sugar factories in Indonesia not only produce sugar made from sugar cane, but also

produce sugar made from raw sugar. Sugar made from sugar cane is known as white crystal

sugar, while sugar made from raw sugar is known as refined crystal sugar. Refined crystal

sugar has been produced in Indonesia since 2003. The development of white crystal sugar and

refined crystal sugar production can be seen in Table 11.

Based on the data in Table 11, white crystal sugar production experienced lower

growth compared to refined crystal sugar production. White crystal sugar continued to

experience a decline in production from 2008 to 2011 and then experienced an increase in

production in 2012.

1.1. Development of Sugar Consumption in Indonesia

Sugar is one of the commodities that is quite strategic and plays an important role in

the agricultural sector, especially the plantation subsector in the national economy because in

addition to being one of the basic needs of the community, sugar also functions as a relatively

cheap food source of calories. Sugar, which is one of the staple foods, always experiences an

increase in consumption from year to year. Consumer dependence on sugar consumption is

quite large because there is little tendency to substitute sugar with artificial sugar or other

sweeteners. The national demand for sugar will continue to increase along with the increase in

population, public income, and the growth of the food and beverage processing industry

(Billah, 2013).

Indonesia is a country that still adheres to sugar dualism, where sugar consumption in

Indonesia is differentiated based on its use, namely direct or household sugar consumption

and industrial sugar consumption. White crystal sugar is sugar intended for household

consumers, while refined crystal sugar is not allowed for household consumption and only the

industrial sector uses this type of sugar (Rahman, 2013).

In general, sugar consumption figures are not specifically monitored such as

production, imports, stocks, and distribution. Because of this, the consumption calculation is

approximated from the distribution figure (Nusantara Sugar Club, 2014). Based on the

balance of sugar consumption in Indonesia in Table 12, sugar consumption has increased

from year to year except in 2010. National sugar consumption from the distribution approach

has increased from 4,278 million tons in 2008 to 5,358 million tons in 2013.

White crystal sugar consumption fluctuates annually, while refined crystal sugar

consumption tends to increase from year to year. According to Rahman (2013), the growth of

refined crystal sugar consumption which is higher than white crystal sugar is due to the

increase in national production of refined crystal sugar which is higher than the national

production of white crystal sugar.

1.2. Indonesia's Sugar Trade Balance

Sugar trade performance on an international scale is approached from the sugar trade

balance, which is the difference between exports and imports. Sugar exports and imports are

carried out in the form of molasses, raw sugar, and other sugar product derivatives which are

a form of manufacturing. The development of the sugar trade balance over the past five years,

namely 2008-2012, shows a deficit position, which means that the volume and value of sugar

imports are greater than the volume and value of exports. The development of the sugar trade

balance can be seen in Table 13.

Based on the data in Table 13, the sugar trade deficit tends to increase from year to

year, especially in 2011 and 2012. This is thought to be because production in the previous

years, namely 2010 and 2011, was lower than in previous years (Billah, 2013). The trade

balance deficit in terms of volume increased by 31.92 percent where the growth in export

volume decreased by 21.22 percent per year while the import volume increased by 31.87

percent per year. Increase in import volume In 2011 and 2012, the average increase in the

trade volume deficit was high. The trade deficit in terms of value also increased with an

average increase of 51.41 percent per year where the increase in export value was only 3.67

percent per year compared to the increase in import value of 51.34 percent per year. The

largest sugar trade deficit in the 2008-2012 period occurred in 2011, which amounted to US$

1.64 billion. This was due to the increase in import volume in 2011 which reached 2.37

million tons with an import value of US$ 1.64 billion.

In order to analyze the competitiveness of Indonesian cane sugar commodities in the

world market, the Trade Specialization Index (ISP) can be used. Based on data on the export

and import values of Indonesian cane sugar, the Trade Specialization Index (ISP) can be

obtained which is presented in Table 14.

Based on Table 14, Indonesia's cane sugar commodity did not have strong

competitiveness in the world market during the period 2008-2012 or Indonesia entered as a

cane sugar importing country. This is indicated by the value of the Index of Trade

Specialization (ISP) of cane sugar which is negative. Based on its growth rate in trade,

Indonesia's cane sugar commodity has reached an importing stage where the supply of cane

sugar in the domestic market is smaller than the demand for cane sugar from domestic

production which is still on a small scale so that Indonesia needs to import cane sugar. The

low ISP value indicates that Indonesia has weak competitiveness for cane sugar commodities

(Billah, 2013).

Indonesia's dependence on sugar imports in 2008-2012 is indicated by the value of the

Import Dependency Ratio (IDR) of sugar which ranged from 27.84 percent to 51.38 percent.

The IDR value in 2008 of 27.84 percent indicates that 27.84 percent of domestic sugar needs

were met by imports. In the following years, the IDR value tended to increase until it reached

51.38 percent. In 2012, the IDR value decreased compared to 2011 to 51.35 percent, which

means that dependence on imports continued but decreased. Dependence on imports still

occurs because domestic sugar production is still unable to meet domestic needs.

In 2008, the Self Sufficiency Ratio (SSR) value of Indonesia's cane sugar commodity

reached 72.20 percent, indicating that national production was able to meet national needs by

72.20 percent. While in 2011 the value of Indonesia's SSR was 48.63 percent, which means

that national production was only able to meet the needs of domestic market demand by 48.63

percent.

Indonesia is a net importer of sugar. Indonesia imports sugar from several countries,

both ASEAN countries and other countries. The volume and value of Indonesia's sugar

imports by country of origin are presented in Table 17. Based on the data in Table 17, the

majority of Indonesia's sugar imports come from ASEAN member countries, namely Thailand

with a volume share of 52.63 percent and a value of 53.75 percent. Brazil is the second largest

sugar export to Indonesia with a volume share of 35.88 percent and a value of 33.88 percent.

Brazil is also the largest sugar producer in the world with a production of 73 400 600 tons in

2011 (Central Bureau of Statistics, 2013).

1.3. Sugar Price Development in Indonesia

Over the past five years (2008-2012) the cost of production (COP) of sugar has

increased from IDR 5 190 per kg in 2008 to IDR 7 900 per kg in 2012 and the cost of goods

sold (COGS) is set 10 percent above the COP. The cost of goods sold (COGS) is the value of

profit for farmers and sales tax for companies. However, the HPP is not followed by the

government as a whole because it is to keep consumer-level prices from burdening consumers

(Nusantara Sugar Club, 2014).

6.1. General Behavior of Model Estimation Results

The econometric model of sugar trade in this study is a dynamic simultaneous model

built from 20 equations, consisting of 13 structural equations and seven identity equations.

The model estimation results in this study are generated through several stages of model

respecification. The data used are annual time series data with observation periods from 1990

to 2012.

Overall, the model estimation shows good results in terms of economic criteria (sign

suitability), statistical criteria, and econometric criteria. Based on economic criteria, each

structural equation has a parameter magnitude and sign in accordance with the hypothesis and

is logical from an economic point of view. Based on statistical criteria, the coefficient of

determination (R2 ) is generally quite high. Most (90 percent) of the structural equations have

a coefficient of determination (R2 ) above 50.00 percent and only one equation has a

coefficient of determination (R2 ) below 50.00 percent with a value of 38.603 percent. This

shows that in general, each endogenous variable diversity can be explained by the diversity of

explanatory variables included in the structural equation.

Based on the F-statistic test, the results show that all structural equations have an F-

statistic test p-value less than α of 15 percent, which means that the explanatory variables in

each structural equation together are able to explain well the endogenous variables. The t-

statistic test results show that with one-way testing individually there are some explanatory

variables that do not significantly affect the endogenous variables at the α level of 15 percent,

but what is prioritized in this study is the logicality and suitability of signs and magnitudes

with economic criteria.

6.1.1. Autocorrelation Test Results

Detection of autocorrelation problems in this study was carried out using DW

statistics and Durbin-h statistics. DW statistical value that obtained in the equation of

smallholder sugarcane plantation area, private large plantation sugar productivity, household

sugar demand, and sugar import volume are 1.5848, 2.1362, 2.6493, and 1.9906. The results

of these values indicate that the equation of productivity of private large plantation sugar and

sugar import volume does not experience autocorrelation problems. The results of the DW

statistical value of the equation of smallholder sugarcane plantation area and household sugar

demand show that the autocorrelation problem in the two equations cannot be concluded

(Pindyck and Rubinfeld, 1998).

The Durbin-h statistical value obtained in the equation of the state sugarcane

plantation area, private sugarcane plantation area, smallholder plantation sugar productivity,

real price of imported sugar, real price of sugar at the w h o l e s a l e r level, and real price of

sugar at the farmer level is -3.3934, - 1.5138, 0.3398, 0.8131, 0.8904, and -0.0932. Based on

these results, it can be stated that the equation of the area of private sugarcane plantations, the

productivity of smallholder plantation sugar, the real price of imported sugar, the real price of

sugar at the wholesaler level, and the real price of sugar at the farmer level do not experience

autocorrelation problems, while the results of the Durbin-h statistical value of the state

sugarcane plantation area equation show that there is an autocorrelation problem in the

equation. The value of the Durbin-h statistic in the equation of the productivity of large state

plantation sugar, industrial sugar demand, and the real price of sugar at the consumer level

cannot be detected because the conditions are not met. The requirement is that the product of

the number of sample observations (T) with the square of the standard error of the coefficient

of the lagged endogenous variable (var(β)) must be less than one, while the results obtained

in the three models are greater than one. This indicates that some equations cannot be

concluded from the autocorrelation problem. Pindyck and Rubinfeld (1998) explained that

autocorrelation problem only reduces the efficiency of parameter estimation and does not bias

the regression parameter estimation.

6.1.2. Multicollinearity Test Results

The multicollineariy problem in the model is identified by looking at the VIF value.

The VIF value is obtained from the regression output using SAS/ETS. Most of the

explanatory variables contained in each of the equation There is one explanatory variable that

has a VIF value of more than 10, namely the lagged endogenous variable in the industrial

sugar demand equation (Table 7). This indicates that one explanatory variable has a

multicollineariy problem, but the multicollineariy problem will only reduce the efficiency of

parameter estimation and does not bias the estimation of regression parameters (Pindyck and

Rubinfeld, 1998).

6.1.3. Heteroscedasticity Test Results

Based on the heteroscedasticity test using the park method, the results show that most

(90 percent) of the structural equations transformed into natural logarithm form produce

probability-t values that have no significant effect at the α level of five percent (Appendix 9).

This indicates that in the model built there is no heteroscedasticity problem in the data used.

Meanwhile, one other equation cannot detect heteroscedasticity problem because most of the

data contained in the independent variable is negative so that the data cannot be transformed

into natural logarithm form. According to Pindyck and Rubinfeld (1998), heteroscedasticity

problem will only reduce the efficiency of parameter estimation but will not cause bias in

regression parameter estimation and inconsistent results.

6.2. Sugarcane Plantation Area

The equation of sugarcane plantation area in Indonesia is divided into three equations

based on the status of plantation exploitation, namely: (1) equation of smallholder sugarcane

plantation area, (2) equation of state sugarcane plantation area, and (3) equation of private

sugarcane plantation area.

6.2.1. Sugarcane Plantation Area

The coefficient of determination (R2 ) of the equation of smallholder sugarcane

plantation area is 0.73401. This means that 73.401 percent of the diversity of the area of

sugarcane plantations can be explained by the diversity of explanatory variables in the

equation, while 26.599 percent of the diversity of the area of sugarcane plantations is

explained by the diversity of other variables that are not included in the equation contained in

the equation. The explanatory variables together are able to explain well the endogenous

variable of smallholder sugarcane plantation area with a prob-F value of 0.0004 (Table 18).

The results of parameter estimation of the area of smallholder sugarcane plantations

show that of the five explanatory variables used in the equation, there are four variables that

have a real effect, namely the real price of sugar at the farm level, changes in the real price of

grain at the farm level, the real price of urea fertilizer, and changes in the production capacity

of sugar factories. The real wage of plantation sector labor has no significant effect on the

area of smallholder sugarcane plantations at the α level of 15 percent.

The real price of sugar at the farm level has a positive effect on the area of smallholder

sugarcane plantations with an estimated coefficient value of 0.02218. This means that an

increase in the real price of sugar at the farm level by Rp 1/ton will increase the area of

smallholder sugarcane by 0.02218 ha, ceteris paribus. Changes in the real price of grain at the

farm level negatively affect the area of smallholder sugarcane plantations with an estimated

coefficient value of 0.04157. This means that an increase in the change in the real price of

grain at the farm level by Rp 1/ton will reduce the area of smallholder sugarcane by 0.04157

Ha, ceteris paribus. The real price of urea fertilizer negatively affects the area of sugarcane the

area of smallholder sugarcane plantations with an estimated coefficient value of 0.08622. This

means that an increase in the real price of urea fertilizer by Rp 1/ton will reduce the area of

smallholder sugarcane by 0.08622 Ha, ceteris paribus. Changes in sugar factory production

capacity have a positive effect on the area of smallholder sugarcane plantations with an

estimated coefficient value of 1.19524. This means that an increase in the change in sugar

factory production capacity by 1 ton/day will increase the area of smallholder sugarcane by

1,195236 Ha, ceteris paribus.

The real wage of plantation sector labor has no statistically significant effect at the α

level of 15 percent on the area of smallholder sugarcane plantations. This is because many

farmers use family labor. Business activities with employment status as family labor occur

due to the problem of limited availability of labor outside the family so that the availability of

labor within the family is used for productive activities to help the family and in accordance

with their abilities (Sugiarto, 2011).

6.2.2. State Sugarcane Plantation Area

The coefficient of determination (R2 ) of the state sugarcane plantation area equation is

0.52995. This means that 52.995 percent of the diversity of the state sugarcane plantation area

can be explained by the diversity of the explanatory variables in the equation, while 47.005

52.995 percent of the diversity of the state sugarcane plantation area is explained by the

diversity of other variables not contained in the equation. The explanatory variables together

are able to explain well the endogenous variable of state sugarcane plantation area with a

prob-F value of 0.0224 (Table 19).

The parameter estimation results of the state sugarcane plantation area show that of the

five explanatory variables used in the equation, there are three variables that have a real

effect, namely the real price of sugar at the wholesaler level in the previous year, the real price

of urea fertilizer, and the real wage of plantation sector labor. The previous year's real credit

interest rate and the previous year's state sugarcane plantation area had no significant effect on

the state sugarcane plantation area at the α level of 15 percent.

The real price of sugar at the wholesaler level in the previous year had a positive effect

on the state sugarcane plantation area with an estimated coefficient value of 0.00712. This

means that an increase in the real price of sugar at the wholesaler level in the previous year by

Rp 1/ton will increase the country's sugarcane area by 0.00712 Ha, ceteris paribus. The real

price of urea fertilizer negatively affects the state sugarcane plantation area with an estimated

coefficient value of 0.01825. This means that an increase in the real price of urea fertilizer by

Rp 1/ton will decrease the state su ga r ca n e a re a by 0.01825 Ha, ceteris paribus. The real

wage of plantation sector labor negatively affects the area of state sugarcane plantations with

an estimated coefficient value of 1.24576. This means that an increase in labor wages by Rp

1/day will reduce the state sugarcane area by 1.24576 Ha, ceteris paribus.

The previous year's real credit interest rate had no statistically significant effect at the

α level of 15 percent on the state sugarcane plantation area. This is because the increase in the

area of state sugarcane plantations is more determined by government policy so that it does

not rely on banks as a source of capital (Rahman, 2013). Plantation area The previous year's

state sugarcane has no significant effect at the α level of 15 percent on the state sugarcane

plantation area. This indicates that there is no grace period required by the state sugarcane

plantation area to readjust to its equilibrium level in response to developments in the domestic

and world sugar economic situation.

6.2.3. Private Sugarcane Plantation Area

The coefficient of determination (R2 ) of the equation of private sugarcane plantation

area is 0.87160. This means that 87.160 percent of the diversity of private sugarcane

plantation area can be explained by the diversity of the explanatory variables in the equation,

while 12.84 percent of the diversity of private sugarcane plantation area is explained by the

diversity of other variables not included in the equation. The explanatory variables together

are able to explain well the endogenous variable of private sugarcane plantation area with a

prob-F value of <.0001 (Table 20).

The results of the parameter estimation of the area of private sugarcane plantations

show that of the five explanatory variables used in the equation, there are two variables that

have a real effect, namely the production capacity of sugar factories and the area of private

sugarcane plantations in the previous year. Changes in the real price of sugar in the consumer

level, the real lending rate, and changes in the real price of urea fertilizer have no significant

effect on the area of private sugarcane plantations at the α level of 15 percent.

Sugar factory production capacity has a positive effect on the area of private sugarcane

plantations with an estimated coefficient value of 0.26591. This means that an increase in

sugar production capacity by 1 ton/day will increase the area of private sugarcane by 0.26591

Ha, ceteris paribus. The response of sugar factory production capacity is inelastic in the short

term, but elastic in the long term, with an elasticity value of 3.15157, meaning that if the

production capacity of the sugar factory increases by one percent, it will increase the area of

private sugarcane plantations by 3.15157 percent in the long term, ceteris paribus. The

variable of private sugarcane plantation area in the previous year has a real effect. This

condition indicates that the area of private sugarcane plantations requires a relatively slow

deadline to adjust in response to developments in the domestic and world sugar economic

situation.

Changes in the real price of sugar at the consumer level have no statistically

significant effect at the α level of 15 percent on the area of private sugarcane plantations. This

is expected because the area of private sugarcane plantations is a farming investment whose

decision does not depend on prices that tend to fluctuate but is more influenced by investment

variables such as the production capacity of sugar factories. Real credit interest rates have no

statistically significant effect at the α level of 15 percent on the area of private sugarcane

plantations. This is because government policy in terms of providing credit for sugarcane

farming is often late or inadequate. The difficulty of credit for sugarcane farming occurs

because sugarcane farming is relatively longer than other food crop farming such as rice, so

sugarcane farming is considered to have a relatively long credit repayment period (Susila,

2005). Changes in the real price of urea fertilizer had no statistically significant effect at the α

level of 15 percent on the area of private sugarcane plantations. This is because private

sugarcane plantations have strong capital resilience so that an increase in the real price of urea

fertilizer does not make the plantation more profitable Private sugarcane reduces the quantity

of inputs so that it does not reduce its area (Rahman, 2013).

6.2.4. Hablur Sugar Productivity of Smallholder Plantations

The coefficient of determination (R2 ) of the sugar productivity equation of

smallholder plantations is 0.83932. This means that 83.932 percent of the diversity of sugar

productivity of smallholder plantations can be explained by the diversity of explanatory

variables in the equation, while 16.068 percent of the diversity of sugar productivity of

smallholder plantations is explained by the diversity of other variables not contained in the

equation. The explanatory variables together are able to explain well the endogenous variable

of sugar productivity of smallholder plantations with a prob-F value of <.0001 (Table 21).

The results of the estimation of the productivity parameters of sugar cane plantations

show that of the five explanatory variables used in the equation, there are two variables that

have a real effect, namely the Indonesian sugarcane yield and the productivity of sugar cane

plantations in the previous year. The area of smallholder sugarcane plantations, Indonesian

rainfall, and time trend are not significant.

Indonesian sugarcane yield has a positive effect on the productivity of smallholder

plantation cane sugar with an estimated coefficient value of 0.68168. This means that an

increase in Indonesian sugarcane yield by one percent will increase the productivity of

plantation sugar by 0.68168 tons/Ha, ceteris paribus. The response of Indonesian sugarcane

yield is inelastic in the short term, but elastic in the long term, namely with an elasticity value

of 4.42305, meaning that if the Indonesian sugarcane yield increases by one percent, it will

increase the productivity of smallholder plantation sugar by 4.42305 percent in the long term,

ceteris paribus. The productivity variable of the previous year's estate sugar has a real effect.

This condition shows that the productivity of smallholder plantation sugar requires a

relatively slow deadline to adjust in response to developments in the domestic and world

sugar economic situation.

The area of smallholder sugarcane plantations did not have a statistically significant

effect at the α level of 15 percent on the productivity of smallholder plantation sugar. This is

because government policies that are biased towards the non-agricultural sector make it

increasingly difficult to obtain suitable land for sugarcane farming so that the added sugarcane

area is located further from the sugar factory (Susila, 2005). Indonesian rainfall did not have a

statistically significant effect at the α level of 15 percent on the productivity of smallholder

plantations. This indicates that the increase in the productivity of smallholder plantations is

not only influenced by Indonesian rainfall. The time trend has no statistically significant

effect at the α level of 15 percent on the productivity of smallholder plantation sugar. This is

because smallholder sugarcane farmers still plant old varieties with lower productivity than

new varieties. Smallholder sugarcane farmers also do not rejuvenate regularly so that the

sugarcane plants owned are generally keprasan plants (Susila, 2005).

6.2.5. Raw Sugar Productivity of Large State Plantations

The coefficient of determination (R2 ) of the equation for the productivity of large state

plantation sugar is 0.58114. This means that 58.114 percent of the diversity of the

productivity of large state plantation sugar can be explained by the diversity of explanatory

variables in the equation, while 41.886 percent of the diversity of the productivity of large

state plantation sugar can be explained by the diversity of other variables not contained in the

equation. The explanatory variables together are able to explain well the endogenous variable

of sugar productivity of large state plantations with a prob-F value of 0.0100 (Table 22).

The results of estimating the parameters of the productivity of state plantation cane

sugar show that of the five explanatory variables used in the equation, there are three

variables that have a significant effect, namely Indonesian rainfall, Indonesian sugarcane

yield, and time trend. The country's sugarcane plantation area and the previous year's sugar

productivity of the country's large plantations do not significantly affect the sugar productivity

of the country's large plantations at the α level of 15 percent.

Indonesian rainfall negatively affects the productivity of sugar hablur of large state

plantations with an estimated coefficient value of 0.00023. This means that an increase in

Indonesian rainfall by 1 mm/year will reduce the productivity of large state plantations by

0.00023 tons/Ha, ceteris paribus. Indonesian sugarcane yield has a positive effect on the

productivity of large state plantations with an estimated coefficient value of 0.49930. This

means that an increase in Indonesian sugarcane yield by one percent will increase the

productivity of large state plantations by 0.49930 tons/Ha, ceteris paribus. The response of

Indonesia's sugarcane yield is inelastic in the short term, but elastic in the long term, with an

elasticity value of 1.05017, meaning that if Indonesia's sugarcane yield increases by one

percent, it will increase the productivity of large state plantations by 1.05017 percent in the

long term, ceteris paribus. Technological improvement proxied by the time trend has a

positive effect on the productivity of large state plantations with an estimated coefficient

value of 0.03815. This means that an increase in technology proxied by the time trend by one

unit will increase the productivity of large state plantations by 0.03815 tons/Ha, ceteris

paribus.

The area of state sugarcane plantations does not have a statistically significant effect at

the α level of 15 percent on the productivity of large state plantations. This means that an

increase in the area of state sugarcane plantations is not a benchmark for increasing the

productivity of state sugar. The previous year's productivity of large state plantations does not

have a statistically significant effect at the α level of 15 percent on the productivity of large

state plantations. This indicates that there is no grace period required by the productivity of

large state plantations to readjust to its equilibrium level in response to developments in the

domestic and world sugar economic situation.

6.2.6. Raw Sugar Productivity of Large Private Plantations

The coefficient of determination (R2 ) of the equation for the productivity of large

private plantation sugar is 0.38603. This means that 38.603 percent of the variation in the

productivity of large private plantation sugar can be explained by the diversity of the

explanatory variables in the equation, while 61.397 percent of the diversity of the productivity

of large private plantations is explained by the diversity of other variables not included in the

equation. The explanatory variables are jointly able to explain well the endogenous variable

of private large plantation sugar productivity with a prob-F value of 0.0292 (Table 23).

The results of the estimation of the productivity parameters of sugar cane of large

private plantations show that of the three explanatory variables used in the equation, all of

them have a significant effect at the α level of 15 percent. The three explanatory variables are

the area of private sugarcane plantations in the previous year, Indonesian rainfall, and

Indonesian sugarcane yield.

The previous year's private sugarcane plantation area has a positive effect on the

productivity of large private plantations with an estimated coefficient value of 0.00002. This

means that an increase in the area of private sugarcane plantations in the previous year by 1 Ha

will increase the productivity of large private plantations by 0.00002 tons/Ha, ceteris paribus.

Indonesian rainfall negatively affects the productivity of large private sugar plantations with

an estimated coefficient value of 0.00038. This means that an increase in Indonesian rainfall

by 1 mm/year will decrease the productivity of large private plantations by 0.00038 tons/Ha,

ceteris paribus. Indonesian sugarcane yield has a positive effect on the productivity of large

private plantations with an estimated coefficient value of 0.00038 tons/Ha.

205

of 0.87056. This means that an increase in Indonesia's sugarcane yield by one percent will

increase the productivity of large state plantations by 0.87056 tons/Ha, ceteris paribus. The

response of Indonesian sugarcane yield is elastic in the short term, with an elasticity value of

1.02284, meaning that if the Indonesian sugarcane yield increases by one percent, it will

increase the productivity of large private plantations by 1.02284 percent in the short term,

ceteris paribus.

6.3. Sugar Import Volume

The coefficient of determination (R2 ) of the sugar import volume equation is 0.76155.

This means that 76.155 percent of the diversity of sugar import volume can be explained by

the diversity of the explanatory variables in the equation, while 23.845 percent of the diversity

of sugar import volume is explained by the diversity of other variables not in the equation.

The explanatory variables together are able to explain well the endogenous variable of sugar

import volume with a prob-F value of <.0001 (Table 26).

The results of the sugar import volume parameter estimation show that of the three

explanatory variables used in the equation, all of them have a significant effect at the α level

of 15 percent. The three explanatory variables are domestic sugar demand, the real price of

imported sugar multiplied by the real exchange rate, and the previous year's sugar import

tariff.

Domestic sugar demand has a positive effect on sugar import volume with an

estimated coefficient value of 0.39981. This means that an increase in domestic sugar demand

by one ton will increase the volume of sugar imports by 0.49404 tons, ceteris paribus. The

response of domestic sugar demand is elastic in the short term, with an elasticity value of

1.21453, meaning that if domestic sugar demand increases by one percent, it will increase the

volume of sugar imports by 1.21453 percent in the short term, ceteris paribus. The real price

of imported sugar multiplied by the real exchange rate negatively affects the volume of sugar

imports with an estimated coefficient value of 0.10443. This means that an increase in the real

price of imported sugar by IDR 1/ton will decrease the volume of sugar imports by 0.10443

tons, ceteris paribus. The previous year's sugar import tariff negatively affects the volume of

sugar imports with an estimated coefficient value of 30161.5. This means that an increase in

the previous year's sugar import tariff by one percent will decrease sugar import volume by

30161.5 tons, ceteris paribus.

6.4. Real Price of Imported Sugar

The coefficient of determination (R2 ) of the real price of imported sugar equation is

0.93559. This means that 93.559 percent of the diversity of the real price of imported sugar

can be explained by the diversity of the explanatory variables in the equation, while 6.441

percent of the diversity of the real price of imported sugar is explained by the diversity of

other variables not in the equation. The explanatory variables together are able to explain well

the endogenous variable of the real price of imported sugar with a prob-F value of <.0001

(Table 27).

The results of the parameter estimation of the real price of imported sugar show that of

the three explanatory variables used in the equation, all of them have an effect real at the α

level of 15 percent. The three explanatory variables are sugar import volume growth, real

world sugar price, and the real price of imported sugar in the previous year.

The growth of sugar import volume has a positive effect on the real price of imported

sugar with an estimated coefficient of 0.07070. This means that an increase in sugar import

volume growth by one percent will increase the real price of imported sugar by 0.07070

US$/ton, ceteris paribus. The real world sugar price has a positive effect on the real price of

imported sugar with an estimated coefficient value of 1.30219. This means that an increase in

the real world price of sugar by 1 US$/ton will increase the real price of imported sugar by

1.30219 US$/ton, ceteris paribus. The response of the real world sugar price is inelastic in the

short term, but elastic in the long term, with an elasticity value of 1.92750, meaning that if the

real world sugar price increases by one percent, it will increase the real price of imported

sugar by 1.92750 percent in the long term, ceteris paribus. The real price variable of imported

sugar in the previous year has a real effect. This condition indicates that the real price of

imported sugar requires a relatively slow deadline to adjust in response to developments in the

domestic and world sugar economic situation.

6.5. Real Price of Sugar at Consumer Level

The coefficient of determination (R2 ) of the equation for the real price of sugar at the

consumer level is 0.75090. This means that 75.090 percent of the diversity of the real price of

sugar at the consumer level can be explained by the diversity of the explanatory variables in

the equation, while 24.910 is explained by the diversity of other variables not contained in the

equation. The explanatory variables together are able to explain well the endogenous variable

205

of the real price of sugar at the consumer level with a prob-F value of <.0001 (Table 28).

The results of estimating the parameters of the real price of sugar at the consumer level

show that of the three explanatory variables used in the equation, there are two variables that

have a significant effect, namely domestic sugar demand and the real price of sugar at the

consumer level in the previous year. The previous year's Indonesian sugar supply does not

significantly affect the real price of sugar at the consumer level at the α level of 15 percent.

Domestic sugar demand has a positive effect on the real price of sugar at the consumer

level with an estimated coefficient of 0.65029. This means that an increase in domestic sugar

demand by one ton will increase the real price of sugar at the consumer level by IDR

0.65029/ton, ceteris paribus. The real price variable of sugar at the consumer level in the

previous year has a r e a l effect. This condition indicates that the real price of sugar at the

consumer level requires a relatively slow timeline to adjust in response to developments in the

domestic and global sugar economy.

The previous year's Indonesian sugar supply has no statistically significant effect at the

α level of 15 percent on the real price of sugar at the consumer level. This means that an

increase in Indonesian sugar supply is not a benchmark for an increase in the real price of

sugar at the consumer level.

Conclusions:

1. Factors that affect the supply, demand, and price of sugar are:

a. Sugar supply is influenced by production, imports, exports, and sugar stocks. Sugar

production is influenced by the area of sugarcane plantations and their productivity. The area

of smallholder sugarcane plantations is influenced by the real price of sugar at the farm level,

changes in the real price of grain at the farm level, the real price of urea fertilizer, and changes

in the production capacity of sugar factories. The productivity of sugar cane plantations is

influenced by Indonesia's sugar cane yield and the productivity of sugar cane plantations in

the previous year. The area of state sugarcane plantations is influenced by the real price of

sugar at the wholesaler level in the previous year, the real price of urea fertilizer, and the real

wage of plantation sector labor. The sugar productivity of large state plantations is influenced

by Indonesian rainfall, Indonesian sugarcane yield, and time trends. The area of private

sugarcane plantations is influenced by the production capacity of sugar factories and the area

of private sugarcane plantations in the previous year. Private large plantation sugar

productivity is influenced by the previous year's private sugarcane plantation area, Indonesian

rainfall, and Indonesian sugarcane yield. Sugar import volume is influenced by domestic

sugar demand, the real price of imported sugar multiplied by the real exchange rate, and the

previous year's sugar import tariff.

b. Domestic sugar demand is influenced by household sugar demand and industrial sugar

demand. Household sugar demand is influenced by the real price of sugar at the consumer

level, changes in Indonesia's population, and per capita income. Industrial sugar demand is

i n f l u e n c e d by time trends and the previous year's industrial sugar demand.

c. The real price of imported sugar is influenced by the growth of sugar import volume, the real

world price of sugar, and the real price of imported sugar in the previous year. Price The real

price of sugar at the consumer level is influenced by domestic sugar demand and the real price

of sugar at the consumer level in the previous year. The real price of sugar at the wholesaler

level is influenced by the real price of sugar at the consumer level and the real price of sugar

at the wholesaler level in the previous year. The real price of sugar at the farm level is

influenced by the real price of sugar at the wholesaler level.

2. The implementation of a policy of reducing and eliminating sugar import tariffs, increasing

sugar stocks, and a combination of reducing sugar import tariffs and increasing sugar stocks

will increase sugar supply, domestic sugar demand, sugar import volume, and the real price of

imported sugar, while the real price of sugar at the consumer level, the real price of sugar at

the wholesaler level, and the real price of sugar at the farm level will decrease. The policy of

increasing sugar prices at the farm level and the combination of the policy of eliminating

sugar import tariffs and the policy of increasing sugar prices at the farm level will increase the

real price of sugar at the farm level, sugar supply, domestic sugar demand, sugar import

volume, and the real price of imported sugar, while the real p ri c e of s u ga r at t h e

consumer level and the real price of sugar at the wholesaler level will decrease.

3. The reduction and elimination of sugar import tariffs will reduce producer surplus and

government revenue, while the increase in sugar prices at the farm level and the increase in

sugar stocks can compensate for the decrease in producer surplus and government revenue so

as to increase welfare (net surplus). The policy that can compensate for the decrease in

producer surplus and government revenue due to the reduction and elimination of sugar

import tariffs is the policy of increasing sugar prices at the farm level. An increase in the price

of sugar at the farm level will increase the net surplus so that the net surplus is positive.

ECN 212_ASU_ASSIGNMENT_2024_THE IMPACT OF SUGAR COMMODITY ECONOMIC POLICY ON THE WELFARE OF SUGAR PRODUCERS AND CONSUMERS

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