The Impacts of Increase in the Domestic Petroleum Prices on Cost Production in the Agricultural and Agro-Based Sectors

By Saari, Yusof; Radam, Alias et al. | International Journal of Business and Society, January 2008 | Go to article overview

The Impacts of Increase in the Domestic Petroleum Prices on Cost Production in the Agricultural and Agro-Based Sectors


Saari, Yusof, Radam, Alias, Abdullah, Amin Mahir, International Journal of Business and Society


ABSTRACT

By using an input-output model, the present paper examines the impacts of increase in the domestic petroleum prices on cost production in the Malaysian agricultural and agro-based sectors. This study simulates the different scenarios of the petroleum price changes on sectoral cost production, which comprises of domestic materials cost, imports and labor. The simulation results indicated that the agricultural sector particularly fishing, forestry and logging products, as well as oil palm primary products industries are mostly affected by the increase of the domestic petroleum price. These industries are significantly affected by domestic petroleum price increase because they consume large amount of petroleum products as intermediate inputs in their production process.

Keywords: Input-output analysis; Domestic petroleum price; Leontief price model.

I. INTRODUCTION

Malaysia's economy, like the other developing countries, used large amounts of energy in its production sectors as intermediate inputs especially in the manufacturing and transportation sectors. The expansion in these sectors have increased the final consumption of energy which grew at 7.8 per cent annually from 1,167.1 petajoules1 (PJ) in 2000 to 1,699.8 PJ in 2005 as shown in Table 1. Among the energy types, the petroleum products were intensively used by the production sector, which accounted about 67 per cent of the total energy used in 2005.

Petroleum products are mainly consumed by local industry, transport and household sectors, which absorbed nearly one-half of the total production. The industrial sector is the largest energy consumer, which utilized 37.1 per cent of the total final energy demand in 2000 and increased to 38.2 per cent in 2005. Industries such as rubber, wood, glass, cement and food processing recorded among the highest energy consumers.

Recently, the increase in petroleum product price was among the most topical issues in Malaysia, even though they remained relatively low in comparison to its neighbors in the ASEAN region, except for Brunei. For the last two years there has been a significant rise in the domestic petroleum price in Malaysia. The retail prices of petroleum, diesel and liquefied petroleum gas (LPG) had increased six times as announced by the government from October 2004 to March 2006. Between this period of time, the retail prices of petrol and diesel increased to about 40 per cent from MR 1.37 to MR 1.92 per liter and from MR 0.781 to MR 1.581 per liter, respectively, as shown in Table 2. The main reason that lead the government to cut down the subsidy was to reduce the government's burden from the price subsidy given to consumers, hence the increase in the domestic petroleum product prices. This measure was taken due to the increase of the world crude oil prices and Malaysia imported high volume of the petroleum. By reducing the price subsidy which subsequently increases the retail petroleum and diesel prices, the government expects to save RM4.4 billion a year, and this saving will be spent on other development projects mainly for improving the public transportation systems.

The government's decision to increase the prices of petroleum products caused pressure on consumers and manufacturers in terms of household expenditures and production cost. Higher oil and petroleum prices will definitely have direct and indirect impacts on the national economy. Direct impacts are the increased in the procurement expenses by manufacturers for purchasing oil or petroleum as direct inputs. Besides that, indirect impacts include the changed prices paid for other products and services, which pass along the supply chain due to higher fuel costs in the product prices.

Under normal circumstances, manufacturers tend to increase their goods and services prices as their cost of production increases; thus the increased cost directly affects the consumers. But if the increase in the cost of production is small, manufacturers will normally absorb part of the cost, thus narrowing profit margins. However, the later scenario seldom happens because firms are not willing to narrow their profit margins. As a result of higher prices of goods and services, inflation rate is expected to increase. However, the effects of increase in petroleum prices on sectoral costs of production will depend on interdependencies of industries in the economy. Industries that consume large amount of petroleum based energy as inputs in their production processes are expected to incur higher production costs.

The government has given a special emphasis to revitalize the agricultural sector after the financial crisis in 1997/98. The sector is envisaged to be the third engine of Malaysian economic growth. This emphasis is further strengthened in the Ninth Malaysia Plan. The development of this sector is expected to be a challenging one due to external shocks such as fluctuation of oil prices, therefore requires careful plans, strategies and programs to ensure its success. This sector is also expected to play an important role in order to reduce income inequality problems amongst small farmers, breeders and fishermen through income generation and productivity improvements. Given the challenging economic conditions, the government or policy makers need all the necessary and sufficient information to evaluate their programs and formulate appropriate policies that can realize its aspiration to develop and expand the agricultural and agro-based sectors.

Considering the above scenario, the purpose of this study is to analyze the effects of petroleum price changes on the costs production in the agricultural and agro-based sectors. In addressing this issue, the study examined the effects of increase in the petroleum prices from different scenarios of changes in the domestic petroleum price on cost production. The general equilibrium of the input-output price model, which captured both direct and indirect effects was employed. However, this study did not seek to explain the reasons underlying the increase in petroleum prices.

This paper is structured as follows. Section II outlines the analytical framework of the inputoutput price model used. Section III discusses the data coverage associated with the study as well as detail sectoral classification of agricultural and agro-based sectors. Section IV presents the empirical findings of the price simulations. Concluding remarks follow in section V.

II.ANALYTICAL FRAMEWORK

Input-Output Price Model

An input-output price model developed by Leontief (1951) has been widely used both in developed and developing countries to analyze the nature of cost-price inter-relationships within a single framework. As documented in Miller and Blair (1985), the basic Leontief price model worked by capturing the impact on sectoral prices as a result of change in the factorial or value added costs. Variations of this basic Leontief price model had been developed by several studies such as Ghosh (1964), Moses (1974), Lee, et al. (1977), Polenske (1978), Young (1978) and Pai (1979). These variations fall into three categories; (i) disaggregated value added component into several categories, (ii) considered changes in sectoral output prices as exogenous instead of value added, and (iii) combination of both Leontief price and output model to determine the total impact. Recently, by using the same approach, Han, et al. (2004) investigated the potential impact of the increase in electricity rates on the Korean economy. Moreover, Valadkhani and Mitchell (2002) applied the inputoutput price model to assess the petroleum price shocks on inflation and household expenditures in Australia. While previous studies fully applied the input-output price model, this study adopted the cost-based input-output model which was introduced by Mathur (1977) and later by Rashid (1989). By using this approach, this study examines the impact of petroleum price on costs productions by disaggregating the components in the costs production into three categories, which are domestic materials, imported and labor.

Every process production involves the use of combinations of production factors such as domestic materials, labor and capital. The costs of production are the values of inputs used and may be obtained by multiplying the amount of inputs used by their per unit prices (Rashid, 1989). In an input-output analysis, input-output coefficients of a structural matrix describe the amount of inputs used per unit of output. These coefficients multiplied by their input prices would give the cost of production per unit cost of output produced. In order to obtain per unit cost for each sector of the economy, as many prices as the number of sectors indicated by the input-output table is needed.

Similarly, the production statements for a particular sector of an economy would have the values of purchases from other sectors. When each of them is divided by the sector's value of output, the results will give the structure of inputs used in production. Its cost of production would, therefore, equal to the sum of the products of its input coefficients and their respective per unit prices. The cost of production can be represented by:

Σ^sub j^ α ^sub ij^ P^sub j^ (1)

where aij and Pj are column vector of sector j inputs coefficients and the producer prices of the respective input for the total of n sectors, i is the sector providing inputs to sector j.

Costs of Production

This model identified three components of total costs; domestic materials, imported input and labor. The structure of each of the first two inputs is represented by their respective input coefficient matrices, namely the structural and imported inputs matrices. Since labor is not normally aggregated by sectors, the structure of labor used in production is represented by its labor coefficient vector. Based on the above formulation, the total cost of production of sector j output that could be expressed as;

Σ^sub j^ P^sub j^ a^sub ij^ + Σ^sub j^ w^sub j^ L^sub j^ + Σ^sup m^^sub j^ P^sup m^^sub j^ P^sup m^^sub j^ a^sub ij^ (2)

where, a^sub ij^ = domestic input coefficient

L^sub j^ = labour input coefficient

ma^sub ij^ = imported input coefficient

P^sub j^ = price of domestic input

w^sub j^ = price of labour

^sup m^P^sub j^ = price of imported input

Equation (2) represents the index of per unit cost of production in sector j in year base year. In addition, due to some limitations in the way the producer prices were provided and the manner in which the model had been developed, all prices of inputs had to be re-expressed in index form.

Cost of Domestic Materials

Let A be the Malaysian 2000 94th order square coefficient matrix whose elements aij being the amounts of output of sector i used by sector j in order produce one unit of sector j output. Suppose that P is the column vector of producer price indices of domestic materials of which indicates the price index domestic material of base year in sector j.

Per unit cost of each sector of the economy can then be represented as:

P'A (3)

The elements of P'A matrix show the annual costs of production for each of the n sectors. By multiplying the column vector of P, the cost of sector j per unit of its output in base year is obtained. This is expressed as;

Σ^sub j^ P^sub j^ a^sub ij^ (4)

Cost of Imported Inputs

The import coefficient maij represents the amount of imported input of sector i purchased by sector j in order to produce one unit of output. When multiplied by the import price of sector j would give the value of imported output of sector i purchased by sector j for each unit of sector j output. Therefore the total cost of imported inputs in year t for producing one unit of j output is the column sum of all the value of imported inputs for each unit sector j output; expressed as:

Σ^sub j^ P^sub j^ a^sub ij^ (5)

Cost of Labour

The cost of labour input is treated separately because the labour coefficient, unlike other two cost items, is represented as a vector because labour cannot be distinguished by sectors. Lj is the labor coefficient representing the amount of salaries and wages paid to produce one unit of sector j output. The annual wage rate wj gives us the value of labour used in order to produce one unit of sector j. When sectoral wage rate is multiplied by the labour coefficients, it will give the value of labour used in order to produce one unit of the sectoral output, or simply called labour costs:

w^sub j^ L^sub j^ (6)

In matrix notation, the annual cost of labour for each n sector for the entire period is obtained by multiplying the column vector of the labor coefficient by the matrix of indices of wage rate that is:

L.W (7)

where L = column vector [Lij] and

W = [wij]

Price Simulations

In this model, the study determined the total per unit cost of production of each sector by three constant coefficients and variables. All the input coefficients that are domestic material, imported inputs and labor are treated as constants, whereas the exogenous variables are the indices of prices of inputs. Since all of the three pairs are constants, the total per unit cost of production after price shocks can be easily determined by substituting new price vectors into base year model of Equation (2). The study simulated different scenarios of the petroleum price changes on sectoral cost of production. In addition, the study analyzed changes in the price of domestic materials only by allowing changes in the petroleum products industry while the price of other components remain unchanged which can be re-expressed via the following equation;

Σ^sub j^ δP^sub j^ a^sub ij^ + Σ^sub j^ w^sub j^ L^sub j^ + Σ^sup m^^sub j^ P^sup m^^sub j^ P^sup m^^sub j^ a^sub ij^ (8)

Since the study only concerned the domestic petroleum products' price effects, in all simulations, it assumes the imports price and labor wage rate are constant, ceteris paribus. In this framework, the study simulates the impact of 30 per cent (simulation I), 60 per cent (simulation II) and 90 per cent (simulation III) increases in the domestic petroleum price on cost production in the agricultural and agro-based sectors respectively.

In the model, while Equation (2) implies that prices in all industries of the input-output table are treated as endogenous variables, in Equation (8), the price in the petroleum products industry is entirely exogenous whereas the prices in the other n-1 industries are endogenous. When the petroleum products price is equal to 1, this implies that there is no deviation in the price of petroleum products industry from its baseline value. However, when for example, the price of petroleum products double, the shock is introduced to the model as 2. Assuming that the petroleum price has doubled, and in solving Equation (8), the resulting price deviations from unity are expressed in percentage, one can determine the impacts of this price shock on the n-1 endogenous industries.

III. SECTORAL CLASSIFICATIONS AND DATA SOURCES

In this study, the main source of the data is from published data of the 2000 input-output (IO) table, which is the latest table published for Malaysia. This table was compiled by using the new industrial classification of the Malaysian Standard Industrial Classification (MSIC) on the basis of the 1993 System of National Accounts (SNA) which was the latest international standard for compiling I-O as proposed by the United Nation. All the transactions recorded in the table were expressed at 2000 basic prices.

The input-output table was compiled for 94 industries, which covered all the industries in the economy. From this table, the study has identified 26 industries within the agricultural and agro-based sectors as shown in Table 3. The primary activities such as palm oil, rubber and livestock are classified under the agricultural industry while the secondary agricultural activities of processing and manufacturing of the primary agriculture such as meat products, dairy product and preserved seafood are categorized under the agro-based sector. Details description of this sector can be referred to in the input-output sectoral classifications in Appendix 1. All the production activities are compiled at 5-digit level of MSIC.

The study also used published data from annual issues of the Industrial Surveys as well as unpublished annual data on the producer price indices for year 2000 from the Department of Statistics, Malaysia (DOS). By using the Malaysia Standard Industrial Classification (MSIC), the study has reclassified the published producer price indices at two-digit level for the domestic production price while import prices are classified by the Standard Industrial Trade Classification (SITC). In cases where more than one prices index (SITC) corresponds to a particular sector in the input-output table, a simple average of them was used to represent that industry's index. They represented the prices of imported inputs in production process.

In estimating the wage rates for various industries, the study prefers to use earning figures to represent wage rates. However, due to the unavailability of such information, price of labor is now defined as the ratio of compensation of employee2 to the number of employees in an establishment. These prices are given in value term, which has to be converted into indices before it can be applied into the model. Then, the compensations of employee figures are obtained from the published figure in year 2000 from the survey conducted by DOS.

IV. RESULTS AND DISCUSSIONS

This section discusses the costs production structure inthe agricultural and agro-based sectors, which were derived from the model. It presents details of the cost structures of different agricultural and agro-based sectors by disaggregating them into cost of domestic materials, imported and labor. Under the assumption that increases in petroleum prices do not affect imported and labor costs, different scenarios of increase in domestic petroleum prices on sectoral cost of production were simulated in this section.

Sectoral Cost of Production

By using the expressions for calculating the cost of production described above, Table 4 shows the results of the agricultural and agro-based indices of total costs. It demonstrates details of cost structures for the different industries in the agricultural and agro-based sectors. These indices represented the cost of production for a unit of output produced by these sectors. Overall, the domestic material inputs represented the largest amount of input used in the production for each ringgit worth of output produced. The livestock, grain mills products and other wood products industries for examples used large amount of domestic materials supplied by other domestic industries in the economy. However, looking at individual sector, the animal feeds and tobacco industries had relied heavily on imported inputs than other agrobased industries. The labor cost represented the least proportion of the industries' total costs.

Results shown in Table 4 revealed that the costs of production of the agricultural sector were lower than the agro-based sector. While half of the agricultural industries consumed large proportion of domestic materials, the oil palm primary products, coconut, tea, and forestry and logging products were recorded to consume a larger amount of labor; implying that these industries were the labor-intensive production. The production cost structures also demonstrated that the agricultural sector used fewer amount of imports in its production process. On the other hand, the cost structures indicated that the agro-based sector consumed larger proportion of domestic materials, followed by imported input and labour. However, the animal feeds and tobacco industries tend to consume a larger amount imported inputs in their production process as compared to domestic materials and labor. This implies that besides utilizing heavily amount of imported inputs, these sectors also have a large leakage to the economy for every unit of increase in its demand.

Our results also showed that the total costs of agricultural industries were lower than those of agro-based industries. The coconut industry for instance, recorded among the lowest costs of production of 0.22673 for every unit of output produced. As shown in Table 4, the agricultural sector experienced low cost of production because of the lower amount of consumption of domestic materials compared to agro-based sector. The cost of domestic materials consumed by agro-based sector on the other hand recorded about two-third of its total production cost. Even though the cost of production in the agro-based sector is higher than the agricultural sector, this sector contributed significantly to the production of other domestic industries in the economy through multiplier and backward linkages effects.

Price Simulations

The variations in the input prices were expected to show corresponding movements in the cost of production through the input-output relationships where the coefficients were fixed. Table 5 shows the results of changes in cost of production resulted from domestic petroleum price level changes. The results obtained were under the assumption that the increase in petroleum prices did not affect labor and import prices. Table 5 shows the total impacts on the cost of production obtained from simulations of three different domestic prices shocks. The price simulations were conducted in three levels of price increase; that is 30%, 60% and 90% respectively.

Overall, the results indicated that the agro-based sector is not significantly affected by the increase in the domestic petroleum prices. In contrast, the simulation results indicated that the agricultural sector particularly fishing, forestry and logging, and oil palm primary products were among the top three industries which were most affected by the increase in the domestic petroleum prices. If the price of petroleum shock were 90 per cent more than current price level, the cost of production for fishing, forestry and logging, and oil palm primary products industries would increase by 30%, 12% and 7% respectively. The increase in the cost of production in these sectors was mainly due to interdependencies among the industries. These industries used large amount of petroleum as intermediate inputs that needed to be procured from petroleum product industry. This highly dependence on petroleum products would influence the cost of production directly whenever the price of petroleum changes.

On the other hand, the results shown in Table 5 revealed that most of the industries in the agrobased sector were less affected by the increase in the domestic petroleum price. For example, the cost of production of a furniture industry only increased to about 0.46 per cent as a result of a 90 per cent increase in the domestic petroleum price (simulation III). This sector was not much affected by the price shock because relatively, it uses less domestic petroleum products as intermediate inputs in their production process.

V. CONCLUSIONS

The study analyzed the impacts of the increase in the domestic petroleum prices on the cost of production in the agricultural and agro-based sectors. Since it employed the input-output model as its basic framework, the study took into account the inter-industry relationships in calculating the sectoral costs of production. The study found that costs of domestic materials represented the largest component of sectoral total costs. The production cost structures revealed that the agricultural sector was still labor intensive, but agro-based sector was more technology-intensive in production processes. Without government interventions or lifting of petroleum price subsidy (90% price increase), the simulation results indicated that fishing, forestry and logging, and oil palm primary products industries would be mostly affected by an increase in the domestic petroleum price. The reason being the consumption of more petroleum products as intermediate inputs in their production process.

The findings of this study will provide useful information to the policy makers with regards to the petroleum price and subsidy policies. Fishing industry will be hit the hardest as petroleum or diesel is the direct input to trawlers of fishing boats. Similarly, petrol or diesel is also a direct input to forestry and logging products industry. It is suggested that special price subsidy which is presented to fishermen be continued to safeguard their socio-economic welfare and sustain their operations. The present petroleum product price policy is rather "fixed" which means that the domestic retail prices are not translated from the world price. Therefore, it is suggested that the domestic retail petroleum price shall be determine in accordance with the movement of the world oil price. The sectoral cost of production will be more competitive as the input prices follow the movement of the world price. Since Malaysia is an oil exporting country, the only setback of this price policy to the government is that the government will incur higher subsidy expenditure when the world oil price falls, given subsidy rate constant.

NOTES

1. Joule is the unit of energy to establish the equivalent physical heat content of each energy form. One metajoule = 106 joules, one gigajoule (GJ) = 109 joules and one petajoules (PJ) = 1015 joules and one PJ = 0.0239 million tones of oil equivalent (mtoe).

2. Compensation of an employee includes remuneration, in cash or in kind, payable by the production activities to employee in return for work done during the accounting period. The components of compensation of employees comprise of wages and salaries, allowances and other payments received in kind.

[Reference]

REFERENCES

Economic Planning Unit. (2006). Ninth Malaysia Plan 2006-2010. Kuala Lumpur: Percetakan Nasional Malaysia Berhad.

Ghosh, A. (1964). Experiments with Input-Output Models. Cambridge: Cambridge University Press.

Han, S.Y., Yoo, S.H., and Kwak, S.J. (2004). The role of the four electric power sectors in the Korean national economy: An input-output analysis. Energy Policy, 32, 1531-1543.

Lee, G.K., Leroy, L.B., and Walter, R.B. (1977). Effects of exogenous prices changes on a regional economy: An input-output analysis. International Regional Science Review, 2, 15-27.

Leontief, W. (1951). The Structure of the American Economy 1919-1939. New York: University Press.

Department of Statistics Malaysia. (1978-2001). The Producer Price Index. Kuala Lumpur: Percetakan Nasional Malaysia Berhad.

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Mathur, P.N. (1977). A study of sectoral prices and their movements in the British economy in an input-output framework. In W. Leontief (Ed.), Structure, system and economic policy (29-47). Cambridge: Cambridge University Press.

Miller, R.E., and Blair, P.D. (1985). Input-Output Analysis: Foundations and Extensions. New Jersey: Prentice-Hall Inc.

Moses, L.N. (1974). Output and prices in interindustry models. Papers of the Regional Science Association, 32, 7-18.

Pai, G.Y. (1979). Environmental pollution control policy: An assessment of regional economics impacts. PhD dissertation, Massachusetts Institute of Technology.

Polenske, K.R. (1978). Energy, analysis and the determination of multiregional prices. Papers of the Regional Science Association, 43, 83-97.

Rashid, Z.A. (1989). Price structure, technological obsolescence and labour productivity - A vintage hypothesis approach. Singapore Economic Review, 34, 50-67.

Valadkhani, A., and Mitchell, W.F. (2002). Assessing the impact of changes in petroleum prices on inflation and household expenditures in Australia. The Australian Economic Review, 35, 122-132.

Young, J. (1978). The multiregional input-output price model applied to transportation. Master thesis, Massachusetts Institute of Technology.

[Author Affiliation]

Mohd. Yusof Saari(a), Alias Radam*b,c and Amin Mahir Abdullah(d)

aDepartment of Economics, Universiti Putra Malaysia, 43400 U PM Serdang, Selangor

bDepartment of Management and Marketing

Faculty of Economics and Management

Universiti Putra Malaysia

43400 UPM Serdang, Selangor

cDeputy Director

Institute of Agricultural and Food Policy Studies

Universiti Putra Malaysia

43400 UPM Serdang, Selangor

dDepartment of Agriculture, Universiti Putra Malaysia, 43400 U PM Serdang, Selangor

* Corresponding author: Alias Radam, Department of Management and Marketing, Faculty of Economics and Management, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor,Malaysia. E-mail: alias@econ.upm.edu.my

(ProQuest: Appendix omitted.)

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