Agricultural Sector and Poverty Incidences. (A Dynamic Computable General Equilibrium Analysis)

Transcription

1 The Impact of Fiscal Policy on Indonesian Macroeconomic Performance, Agricultural Sector and Poverty Incidences (A Dynamic Computable General Equilibrium Analysis) 1. Main Research Questions and Core Research Objectives 1.1 Main Research Questions Indonesian government has set and conducted several remedial measures since the economic crisis However Indonesian government still face three major economic problems that have a crucial implication in the short and middle term, which are (a) an increase of deficit budget, (b) a fluctuation of the exchange rate despite the fact that it tends to a stabile movement and (c) a slow progress of the banking restructuring program. The constantly growing deficit budget provides a pressure on the budget planning, particularly on the expenditure side, because the government has to repay its high foreign debt including its interest rate. The obligation to the foreign creditors causes the deficit budget every year. In addition, the exchange rate to the US dollar that fluctuates unpredictably contributes the government burden in terms of repaying its foreign debt. As the US dollar appreciates to the Rupiah, the government debt increases in terms of the Rupiah. On the other side, the Rupiah experiences a 10 percent depreciation against the US dollar, as a consequence the fuel subsidy increases by 10 percent. A fluctuation of the exchange rate may also cause a price uncertainty in which the business people see as a market risk that leads to an increase in the interest rate. If the interest rate increased followed by an increase in the Certificate of the Indonesian Central Bank (SBI) for instance by 1 percent, the government burden to pay its SBI would increase by 2.3 trillions Rupiah. The burden becomes more aggravated as the government uses the foreign debt for financing the deficit. To overcome such problem, within the government has designed several fiscal policies in order to increase the government revenue and to reduce the expenditure. The policies include (a) an increase in the price of fuel, electricity, and telephone rate. On the revenue side, the government raised the value added tax (VAT) rate from 10 percent to 12.5 percent at June 6 th The government has set monetary policies by setting a floating bond interest rate with the reference to the interest rate of the SBI. Therefore, the monetary authority should take such economic relation into account when adjusting the interest rate. This is because any adjustment in the interest rate leads to the changes in the fiscal position and banking performances. In the other words, a co-ordination between the fiscal authority and the monetary authority, which are in practice difficult to co-ordinate, is highly required. In turn, the difficulty of adjusting the interest rate causes the exchange rate stabilisation difficult to undertake. In such position, the monetary authority faces a difficult choice. On one side, the fiscal policy should be carefully implemented and even measurable to absorb the excess liquidity in order to reduce the inflationary pressure. This pressure will lead to degrading the consumers purchasing power and increasing the poverty incidence. However, on the other side, the absorption of the excess liquidity is required by maintaining the economic recovery measures. The research to be undertaken in this stage will concentrate on the fiscal aspects. In other words, the analysis will be carried out in given monetary conditions. Questions to be asked in this research are (1) in what extent the fiscal policies have impacts on the

2 macroeconomic performances such as employment absorption, investment, consumption, exchange rate, inflation level, real wages, etc., (2) in what extent such policies affect economic sectors, especially agricultural sectors and also the poverty incidence, and (3) what kind of fiscal policies is required to accelerate the economic growth and lift up the poverty existence Core research Objectives In general, this research is directed to examining the impact of the fiscal policies on the macroeconomic variables, the performance of the agricultural sectors and the income distribution or welfare of low-income households. Specifically, the objectives of the research are: (i) To examine the impacts on the macroeconomic performances such as employment absorption, investment, consumption, exchange rate, inflation level, real wages, etc. (ii) To analyse the impacts of the fiscal policies on the performances of the economic sectors, particularly agricultural sectors in terms of the development of outputs, capital accumulation, employment absorption, wages, price forms, income distribution and also on the poverty incidence. (iii) To seek alternative fiscal policies by simulating the current fiscal policies so that the Indonesian stabile economic structure is achieved not only from the point of view of the business environment but also the macroeconomic point of view 2. Scientific Contribution of the Research This applied research will enrich information or knowledge and provide comprehensive analyses of the impacts of the current fiscal policies on the Indonesian economic structure. No literatures or publications are found in the context of the comprehensive analysis of the impacts of the Indonesia fiscal policies on the macroeconomic variables, agricultural sectors and poverty incidences. Besides, a model developed in this research is a dynamic model that is not yet applied for cases in Indonesia. Using the dynamic model, one can get policy simulation results for a short term, middle term and long term for one variable. The research is also important in providing information to the decision makers in the real sector, particularly in terms of the amount of tax and subsidy for agricultural and other sectors. It is hoped that this research will indicate that several kinds of fiscal policies contribute or affect the Indonesian macroeconomic structure and the structure of economic sectors. On the other side, the feed back from each sector to the macroeconomic performance can be analysed. 3. Policy Relevance From the view of the fiscal policy, an increase in the price rate of fuel was one of the government policies to reduce the increasing subsidy burden each year. Since the economic crisis a share of the fuel subsidy to the national expenditure grows sharply. In 1997 its share was 8.7 percent, increasing to 18.1 percent (1998), 21.7 percent (1999) and 26.4 percent (2000). Due to the sharp increase in the fuel subsidy, the government on October 1 st 2000 decided to increase the fuel price by a 12 percent. On June 16 th, 2001 the fuel price was further increased by 30.1 percent. According to the Presidential Decision No 9 on January 16 th, 2002 the prices of the fuel with exception of the kerosene will follow the movement of the world price. As a consequence, domestic consumers will face unstable fuel prices. Low-income households are badly hurt by this policy. Due to their high reliance on the fuel, the increase in the fuel price erodes their purchasing power.

3 Following that decision, consumers have experienced an increase in the fuel prices twice; in April and May For example, the gasoline price was Rp 1 600, kerosene price for large industries was Rp 1 310, and Rp for diesel fuel. Even in May 2002 the increase in the gasoline price nearly approached the level of the ceiling price, that is, Rp while kerosene for industries, and diesel fuel were Rp and Rp respectively. Another fiscal policy implemented in recent years was the reduction of subsidy for electricity. Consequently, the government raised the electricity price level by 17,47 per cent. According to the presidential decision No. 133/2002, the increase in the electricity price was carried out in four stages; stage 1 (January 1 st March 31 st ), stage II (April 1 st June 3 rd ), stage III (July 1 st September 3 rd ), and stage IV (October 1 st December 31 st ). In each stage on average the increase in the price was approximately 6 percent. On the financial side, the government decides to restructure the banking sector. The cost of that policy was estimated around 51 % of the Gross Domestic Product (GDP) (Lindgren, et al, 2000). This number was even the largest one provided by the government among the countries that were hit by the economic crisis. Despite a massive government financial support, the progress of banking restructuring programs was reported quite slowly. Non-performance loan (NPL) for nearly all banking sector was quite high. Their loan portfolio to the real sector was reported very small. As mentioned earlier, to restructure the banking sector the government provided financial support such as the government bond (Rp. 410 trillions). This was equal to 45 percent of the total assets of the banking sector. 4. Literature review There has been several studies examining the impact of fiscal policy ( subsidiy reduction on fuel, electricity and telecomunication) on the Indonesian economy. The issue of such reduction become a central discussion since the signing of Letter of Intent (LoI) between the Indonesian governemnt and the International Monetery Fund (IMF), following the economic crisis. Facing a continuing budget deficit every year the government decided to reduce its subsidy to several commodities that are highly demanded and have a wide impact on the industry output and household consumption patterns. By 2004 all subsidies will be completely abolished. However, most of the studies focused largely on the impact of an increase in fuel, electricity and telecomunication prices on the inflation and production costs, see Institut of Economic Research (2001), Ministry of Finance (2000) and Oktaviani (2001). Using simultaneous equation from the time series data ( ), Institut of Economic Research (2001) noted that the fiscal contraction as represented by a 20 % increase in fuel price would lead to an increased cost of production by 1 % and inflation by 0.5 %. Since the analysis was a partial equilibrium model in nature, the analysis did not identify which types of household would be severely afffected by such policy. The later analysis (Ministry of Finace (2001) and Oktavinani (2001) adapted CGE model to estimate the impact of such fiscal policy. Despite the fact that the model disaggregated households into different types of households, no attempts were made to identify the impact of such policy on the poverty incidence. The only information found in the study of the Ministry of Finance was that the midle and large rural households would be slightly affected by the increased fuel prices as indicated by the decrease in their real consumption; % and % respectively. Hertel, Preckel, Cranfield and Ivanic (2001) estimated poverty incidence using poverty measure proposed by Foster, Greer and Thorbecke (1984). This measure focuses on incomes below poverty level. However, they concentrated largely on the central issue whether trade liberalisation would have impacts on the poverty incidence. The critical level for the post liberalisation scenario is obtained by calculating the income level required to obtain the same

4 utility level as was achieved before liberalisation, but at post liberalisation consumer prices and incomes. Since the GTAP model assumes only one aggregated consumer, they incorporated Indonesia Social-Economic Survey (SUSENAS) data to differentiate households into various household categories based on their sources of income. They found that multilateral trade liberalisation would reduce poverty. The percentage reduction in poverty incidence was particularly striking in the case of labour households in Indonesia (poverty falls by 10.6%). Little is known in what extent the reduced subsidies or no subsidies on fuel, electricity and telecommunication affect the welfare of households and poverty incidence. Therefore a comprehensive analysis is badly needed, especially using a computable general equilibrium model. This is because the impact of such a change in fiscal policy has repercussion effects (general equilibrium effects) for instance on other sectors, employment, and household income distribution. No studies above focused on the changes in fiscal policy and poverty. They have not paid particular attention on the poor and its source of income. It is hoped this study bridges this gap and provides its value added. 5. Methodology The impact on fiscal policy can be evaluated through computable general equilibrium model (CGE). The basic model will be used in the research is INDOF (Oktaviani, 2000) and MAKROEKONOMI (Sugema, 2001). The modification of these models will be built to more focus on the macroeconomic policy change, which is emphasised on the fiscal policy change. Because the new model is different from the basic model, this model will be called DyGEM Sector Aggregation The model will not use all sectors, which are available in the current Indonesian Input-Output Table. Sectors specified in the model include (a) agriculture, forestry and fisheries, (b) mining, (c) manufacturing, (d) constructions, (e) electricity, gas and water, (f) transportation, (g) communication, (h) wholesales and retailers, (i) financial service and housing, and (j) other services 1. The aggregation of sectors as described above refers to the objectives of this research. One of the research objectives is to examine the impact of the subsidy reduction of fuel, electricity and telecommunication on the macroeconomic parameter. Therefore, mining, electricity (including gas and water) and communication sectors are explicitly disaggregated. Explicitly disaggregating the transportation sector is due to the fact that this sector demands fuel. Any increase in the price of transportation cost will have a domino impact of the price of other commodities. According to the Central Bureau of Statistics transport cost or the price transportation means contributes to the inflation rate. Therefore, examining the impact of the subsidy reduction of fuel requires such a sectoral disaggregation. In addition the number of sectors is considered to be manageable and relevant to the research objectives Model Structure Production Structure In the production process, each industry can produce several commodities. Industries use both intermediate and factor inputs. Each intermediate input can be source domestically or imported. Factor inputs for each industry are labour, capital and land. Key simplifying assumption made in this production model include input-output separability and the multistage, hierarchal structure based always on constant elasticity of substitution (transformation) production (transformation) functions except for combining of intermediate goods and aggregate primary factors, a stage which uses the Leontief or fixed proportions technology. 1 The small number of sectors is chosen because the model is the generic one. The more detailed sector aggregation will be generated after model building.

5 Demand for labour Labour is further differentiated by occupation, four in the analyses in the study (farmers, professional, administration and operator). No distinction is made between imported factors and domestic factors, all factors in fact being domestic in origin. Using a Constant Elasticity of Substitution (CES) these types of labour are aggregated into labour composite. The demand for labour of a particular occupational type is proportional to the overall labour demand in the industry and depends on the price of a particular type of labour relative to the average price of labour in that industry. The assumption of factor mobility in the context of a general equilibrium model is very important. If a factor is mobile between sectors, the only difference in prices to the user in different uses would be industry specific factor use taxes or subsidies. On the other hand, if a factor is not mobile but specific to industry, then the prices across industries would not be directly related, but being rents determined by common and/or related product prices, would still be indirectly related. There are four possible labour specification: (a) fully mobile between industries and occupations, (b) mobile only between industries within an occupation, (c) mobile only between occupations within an industry, and (d) all labour in each occupation in each industry is specific to that industry. The study employs the first of these assumptions. This assumption implies that a single economywide average wage rate for each occupation. The assumption of perfect labour mobility seems unrealistic. In fact, the movement of labour types requires some adjustments such as re-training and re-investment and it takes time to take place. In addition, there is an indication that significant and persistent wage differential exist across sectors for the same occupational groups (Maechler and Roland-Holst, 1997) Demand for primary factors The demand by industry for each factor depends on the overall factor demand in that industry and on individual factor prices in the industry relative to the average factor price in that industry. The demand equation of each factor follows from minimising the total factor cost subject to the production function at this level. Changes in the prices of the primary factor relative to an average factor price changes the demand for this labour. The producer will substitute towards the relatively cheaper factors. The degree of substitutability depends on the assumed elasticity substitution between primary factors Demand for intermediate inputs Based on the Armington assumption, imports are imperfect substitution for domestic supplies. In acquiring a given amount of commodity, an industry seeks to minimise the total cost of the imported and domestic goods subject to the CES production function. The selection of the value of the elasticity of substitution plays an important role in determining such a demand. If a very high elasticity of substitution is selected, the responsiveness of the ratio of imported goods to domestic goods will be big, vice versa. Another consequence of using a CES function is that since the price of domestic goods increases relative to imported goods, the users will substitute away from domestic goods in favour of imported goods Demand for intermediate inputs and the composite primary factors. At the highest level of the input side of the production process, the commodity composite, the primary-factor composite and other cost factor are combined in a Leontief production function to determine the level of output activity for the industry. The demand equations for composite primary factor, for intermediate inputs, and the other cost are, under profit maximising behaviour, directly proportional to the level of activity in the industry The commodity composition of industry output The commodity composition of industry output in determined as that maximising the total revenue from all the commodities subject to the level of production activity in the industry using a Constant Elasticity of Transformation (CET) function. In this case, the transformation will move in favour of a commodity if there is an increase in the price of that commodity,

6 relative to the average. The average price received by an industry for its various commodities is a revenue-share-weighted average of the individual prices. This must equal the price of the industry s activity or composite output under zero profits Demand for investment (capital goods) The production function for capital goods is assumed to be multi-staged with a CES function at the bottom level combine different sources of goods and a Leontief production function at a higher level to combine composite intermediate goods. It is assumed that the capital goods can be produced without using primary factors. At the lower stage, the total cost of imported and domestic good is minimised subject to a CES function and particular output level Household demand Because the focus of the research is the impact of the fiscal policy on welfare distribution and income structure, the disaggregation of household groups is important. Therefore the households are divided into six categories based on the household income (low, middle and high) and the place (rural and urban). The household sector is assumed to take prices as given and to consume commodities to maximise a utility function subject to an aggregate expenditure constraint. At the higher level, households choose between different types of commodities in accordance with the linear expenditure system (LES). At the second level, they combine goods from different sources (domestic and imported) through a Constant Elasticity of Substitution (CES) mechanism. Since the model applies the Armington assumption in distinguishing the source of commodities demanded by the end users, the degree of substitution is captured by the so-called Armington elasticities that appear in and must be specified for commodity demand function for different users Export and other final demand For modelling export demand, following ORANI-F, commodities are differentiated into two groups: traditional export and non-traditional export commodities. The specification of export demand in the model differs for two groups. Essentially, the model allows for the independent specification of an own-price dependent demand function for a traditional export commodity, but not for non-traditional exports. For the later, exports are assumed to be in direct proportion to the aggregate of the group of non-traditional exports. A price dependent export demand function is specified for this aggregate. For a traditional export commodity, the demand function is a power (constant elasticity of demand) function Demand for goods as margins While producers, consumers, and other users of commodities use them in accordance with the production/consumption technology, the use of commodities often entails further service inputs. In effect, there are additional inputs, which are not captured by the assumed CES/Leontief/LES production/demand processes. These inputs are the margin goods. The amounts of goods required as margins are assumed to be directly proportional to the commodity flow at the lowest levels of the production/consumption processes Rates of return on capital n this study, the recursive sequence equilibrium approach is used. The term "recursive" refer to the situation in which the current equilibria depend solely on the past or previous equilibria. In this approach, economic agent is endowed with the myopic expectation. It means that the current decision of the economic agent is derived from the information of the past. The most frequently used information is that the economic agent (consumers) is endowed with the capital which is determined by the level of investment. The level of investment and capital stock in the past will link between different static equilibria (Bettendorf, 1994). In the dynamic process, the level of capital stocks becomes very crucial factor. This is because in the

7 static model capital is assumed to be fixed. Letting the dynamic process enter into the model, the demand and supply of capital will change fundamentally. In the model, ORANI specification model (Oktaviani, 2000) will be used. Dixon et al (1982) developed capital creation equations by postulating that investors in an industry expect the future period equilibrium rate of return to creating capital in that industry to be proportional to the current period equilibrium rate of return with the proportionality constant being the ratio of the equilibrium level of capital that will exist in the future in the industry to the current period equilibrium level of capital in the industry. Future period equilibrium capital is definitionally related to current period equilibrium capital as that stock plus net investment. The ratio of next period capital to current period capital is the power of the net rate of capital growth. If capital stocks remain the same from the current to the next period, that is the sector is in a steady state, the current and expected future rates of return are equal Investment-capital accumulation The standard model CGE models have no equation directly relating investment to capital stocks. Only by virtue of imposing conditions on growth rates or through equilibrium conditions imposed on rate of return, do investment and capital stocks become indirectly related. The model includes an equation directly linking pre-existing or time 0 capital stocks T periods hence, or equivalently, directly linking investment and capital stocks in period T Foreign Debt Accumulation The treatment of debt accumulation parallels that of capital accumulation. Over the period 0 to T, the annual trade deficit is implicitly assumed to change in a linear fashion from its initial to final period T level. Debt levels are linked to the accumulated balance of trade deficits, with interest being payable at a world interest rate on the accumulated debt. The debt, trade deficit and interest payments are denominated in base-period foreign currency. The changes in trade deficit and foreign debt will be termed in a proportion to the GDP. The equation essentially adds on the rest of the model sequently rather than being truly simultaneous. That is, the rest of the model essentially determines the balance of trade deficit; this determines the change in debt and this in turn determines the debt ratio. It is clear that the existing trade deficit will be financed through the external debt. As mentioned above, these equations will be used to interpret the results of simulations. In addition, it may be helpful to ensure the model running well what expected Technological Change In the static model, it is assumed that technology change is constant. However, the role of the technological efficiency in the dynamic model plays a crucial factor due to the fact that research elaboration to find a new technology to increase a level of productivity in each sector particularly in the agricultural sector may take place. Thus incorporating the change in the level of technology in the model requires an introduction of a new parameter, called " a parameter of technological change augment" which is sector-specific and exogenously determined. The model developed here is flexible in incorporating factor augmenting technical change Elasticities and other Parameters The source of data for the model is the latest version of Indonesian Input-Output Table (I-O Table) and the latest version of Indonesian Social Accounting Matrix (SAM). And the latest 2 Saving rates of agents are assumed to be constant over time. As a result, the model is an investment-driven model.

8 version of Survey Sosial Ekonomi Nasional (National Social Economic Survey) will be also used to provide household s income and expenditure patterns. The general equilibrium model requires that elasticity parameters and various behavioural parameters to be specified. The elasticity parameters used in the models are the Armington elasticities, the substitution elasticities for labour, the substitution elasticities for primary factors, the export elasticities and the demand expenditure elasticities. Other parameters are related with investment. Ideally, these parameters of the model would be estimated econometrically using time series data. Relatively, little effort has been devoted to this substantial task for Indonesia, in part due to the lack of availability of good time series data (Oktaviani, 2000). As with other CGE modellers the present research relies entirely on the parameters first estimated for other countries but judged to be reasonable guides for Indonesia. The expenditure elasticities are required to calculate the marginal budget share. These elasticities are then scaled in order to make the share weight or an Engel aggregation equal to one, to satisfy the restriction of utility maximisation. Other parameter used in the model is the investment parameter as specified in the ORANI investment model. The parameter specifies the relationship between the rate of return on capital and capital in each producing sector or industry. There is no data available on the investment parameter. Hence, the investment parameter of 5 is taken from the ORANIF model of the Australian economy (Horridge, et al., 1993). Other related parameters will be selected from literature surveys. The GEMPACK computing package will be used to construct the database, calibrate and run the model. In addition, the model is linear in percentage changes. The database will be calibrated to represent the steady-state condition. As a result, the simulation results will be compared to that condition Poverty index As indicated earlier six different types of households will be explicitly specified. These households are endowed with the primary factors such as capital, land and labour. Land is a sector-specific. Agricultural households receive income primarily from agricultural land and agricultural labour. It should be emphasised here that only agricultural sector demands land. There are two aspects concerning the impact of the reduction of government subsidies on fuel, electricity and telecommunication: income and expenditure structures. Income structures that are derived from factor returns represent a primary channel for fiscal policy transmition to poverty. Likewise household s consumption patterns are also predicted by changes in prices of commodities. Both aspects will be closely examined before and after the simulations. It is expected that the increase in prices of commodities following the reduction and even the abolition of subsidies will directly reduce the household s consumption. In addition, such policies will affect the producing sectors, especially the sectors relying heavily on the formerly subsidised intermediate inputs (fuel, electricity and telecommunication). There will be contracting economic sectors. Since these sectors reduce demands for primary factors, households will experience a declining real income. Poverty analysis is sensitive to the choice of fiscal policies for the compensation of the decline in government revenue. The impact of increased budget deficit may be off set by an increased fiscal deficit. The Indonesian government following the signing of the Letter of Intent (LoI) with the IMF will completely abolish all subsidies by Poverty analysis is based on Foster Greer and Thorbecke (F-G-T), P measures, i.e., head count (Po), income gap (P1) and severity index(p2). 6. Data Requirement and Sources

9 Data requiremnet of the model are: a. The lattest version of Indonesian Input-Output Tabel (I-O Table) b. The lattest version of Indonesian Social Accounting Matrix (SAM) c. Behavioral parameters from previous econometrics studies. d. Other statistical data (macroeconomic and sectoral data) Most data can be obtained through the Statistical Bureau, Bank of Indonesia, Ministry of Finance, Library and other national and international institutions. 7. Dissemination Strategy The research can measure the impact of fiscal policy on macroeconomic variable and sectoral economic performance, especially on output, labor mobility and poverty indicators. Because the model is dynamic, the result can be used as the annually forecast of the policy change. The result can be used as a basic measurement of government policy, because the short and long run impact of the policy can be assessed. The research can be used as an academic exercise for the Post Graduate students in order to apply the econometrics and general equilibrium theory on the economic policy simulation. The generic model will be built can be applied in other economic policies, such as monetary and banking policy. The development of the regional model for the next step can also be used to analyse the impact of national policy on regional economy or the impact of regional policy on national and other regions economy. To broader the usefulness of the research, the result of the research will be published in national (Mimbar Sosek, Quarterly Review of the Indonesian Economy) and international scientific journals (Bulletin of Indonesian Economic Studies). The result will also be presented to the Ministry of finance, Ministry of Economic Coordination, and other institutions that is related to the fiscal policy. 8. Short List of key References Bettendorf, Leon. (1994). A Dynamic Applied General Equilibrium Model for a Small Open Economy. Dissertation. Leuven University. Leuven. Departemen Keuangan RI (Indonesian Ministry of Finance). (2000). Mempertahankan Kelangsungan Anggaran Negara (Maintaining The National Budget). Jakarta. Dixon, P.B., Parmenter, B.R., Powell, A.A. and Wilcoxen, P.J. (1992), Notes and Problems in Applied General Equilibrium Economics, North-Holland, Amsterdam. Horridge, J., Parmenter, B.R. and Pearson, K.R. (1993), "ORANI-F: a general equilibrium model of the Australian economy", Economic and Financial Computing 3: Lembaga Penelitian Ekonomi (Institut for Economic Research) IBBI. (2001). Ekonomi Indonesia (Indonesian Macroeconomics). Gramedia. Jakarta. Makro Lindgren, Carl-Johan, Tomas Balino, Charles Enoch, Anne-Marie Gulde, Marc Quintyn and Leslie Teo (2000), 'Financial Sector Crisis and Restructuring: Lessons from Asia', IMF Working Paper 188, International Monetary Fund (June). Maechler, A. M. and D. W. Roland-Holst (1997). Labor Market Structure and Conduct. In Applied Methods for Trade Policy Analysis. A Handbook, edited by J. F. Francois and K. A. Reinert. Cambridge University Press. Cambridge. United Kingdom. Oktaviani, R. (2000), The Impact of APEC Trade Liberalisation on Indonesian Economy and Its Agricultural Sector, Ph.D thesis, The Sydney University.

10 Oktaviani, R. (2001). Dampak Perubahan Kebijakan Fiskal terhadap Kinerja Ekonomi Makro dan Sektoral (Impacts of Changes in Fiscal Policy on Macroeconomic Parameters and Economic Sectors). Bisnis dan Ekonomi Politik. Vol (No): 4(4): Sugema, Iman (2000), Indonesia's Deep Economic Crisis: The role of the banking sector in its origin and propagation, 2000, Ph.D thesis, The Australian National University. 9. Prior Training and Experience of Team Members in the Issues and Techniques Involved 1. Rina Oktaviani She got her PhD from The University of Sydney. Her Dissertation use Multi country, multy commodities CGE model (GTAP) and National CGE model (INDOF). The title of the dissertation is: The Impact of APEC Trade Liberalization on Indonesian Economy and Agricultural Sector (2000). Several courses which are related to the study: a. Practical General Equilibrium Modelling Course, Centre of Policy Studies, Monash University, June, 1997 b. Dynamic Programming Course, The University of Sydney, 21 January 2000 c. Master Class in Economic Policy Modeling, Collaboration between Crawford Fund, ACIAR, Monash University and UGM, Yogyakarta, 26 th 30 th March Hermanto Siregar He got his PhD. in economics, specialising in Macro-econometrics from Lincoln University, New Zealand. He has several publications, which are related to the study (See his Curriculum Vitae). 3. Dedi Budiman Hakim He got his PhD from Institut fuer Agraroekonomie Georg-August-Universitaet Goettingen Germany. His dissertation title is The Implication of the ASEAN Free Trade Area (AFTA) on Agricultural Trade ( A Recursive-dynamic General Equilibrium Analysis). Several courses which are related to the study: a. GAMS Workshop in MuensterGermany1998 b. Agricultural Policy Analysis in Bandung (West Java, Indonesia) and in Jember (East Java) in cooperation with BAPPENAS/USAID/DAI, Sahara She is a Post Graduate Student (Master) in Agricultural Economics, Bogor Agricultural University. She takes the Applied General Equilibrium Analysis Course in her Post Graduate study. She will use CGE model in her propose thesis. 10. Expected Capacity Building for Researchers and Their Institutions The propose research will be an umbrella of the future research which is used CGE model in Bogor Agricultural University. Most of researchers are recently graduated from overseas Doctoral study which need the research environment after going back to their nations. The proposed research will stimulate researchers to build their research capacity. 11. Any ethical, social, gender or environmental issues or risks which should be noted These issues should not be notes in this research