The Impacts of Higher Energy Prices on Indonesia’s and West Java’s Economies using INDOTERM, a Multiregional Model of Indonesia

Indonesia’s national and regional/local policy makers are becoming increasingly concerned with disparities between regions. Aggregate incomes and expenditures in one region may change proportionally more than national changes. This paper contains a technical summary of the structure and special features of INDOTERM model, a member of the TERM family (TERM = The Enormous Regional Model). It treats West Java and the rest of Indonesia as separate economies. We discuss the data required to prepare a version of INDOTERM that represents all the provinces of Indonesia. Finally, we present a long-run simulation of the impacts of the recent hike in global energy prices on the Indonesian economy combined with possible depletion of Indonesia’s crude oil supplies. The special features for future development of INDOTERM are multiple household incomes and expenditures and a “top-down” extension representing sub-provincial municipalities. Nationally, Indonesia’s real income losses due to resource depletion are more than compensated by the sharp increase in the terms of trade arising from the increase in global demand for energy. West Java and the rest of Indonesia fare similarly, as a large proportion of the composite region consists of the remaining provinces of Java which have a similar economic structure to West Java. The relatively sparsely populated outer islands that are relatively rich in mineral resources are not represented separately. Using a “top-down” extension of West Java’s 25 municipalities and districts in INDOTERM, the simulation shows that Kabupaten Indramayu fares best. This local region also loses from the decline in crude oil productivity, and indeed the output loss more than outweighs the increase in natural gas production for this effect. But it gains substantially from the energy price hikes: the increase in nominal income has a substantial positive effect on the municipality, with local industries, including trade and motor repairs experiencing output increases in excess of 40%. Overall, the municipality experiences a gain in factor income of 7.3%, whereas most other regions of West Java lose income in the scenario.Computable General Equilibrium, Regional CGE, Indonesia

CGE modelling of the resources boom in Indonesia and Australia using TERM

The sharp increase in Australia's terms of trade since 2003-04 has dramatic regional and sectoral implications. Mining-intensive regions have gained from the jump in export prices. Import-competing sectors have faced greater competition both from falling import prices and due to rising demand for domestic factors from the mining sectors. The drought of 2006 will widen the gap between winning and losing regions. In Indonesia, even if we assume that the oil extraction sector is facing resource depletion, a long-run terms-of-trade improvement may result in aggregate consumption increasing should real GDP fall relative to the base case. The TERM framework is highly suitable for modelling Brazil and China, each with around 30 regions.Resource /Energy Economics and Policy,

What does the honeybee see? And how do we know?

This book is the only account of what the bee, as an example of an insect, actually detects with its eyes. Bees detect some visual features such as edges and colours, but there is no sign that they reconstruct patterns or put together features to form objects. Bees detect motion but have no perception of what it is that moves, and certainly they do not recognize “things” by their shapes. Yet they clearly see well enough to fly and find food with a minute brain. Bee vision is therefore relevant to the construction of simple artificial visual systems, for example for mobile robots. The surprising conclusion is that bee vision is adapted to the recognition of places, not things. In this volume, Adrian Horridge also sets out the curious and contentious history of how bee vision came to be understood, with an account of a century of neglect of old experimental results, errors of interpretation, sharp disagreements, and failures of the scientific method. The design of the experiments and the methods of making inferences from observations are also critically examined, with the conclusion that scientists are often hesitant, imperfect and misleading, ignore the work of others, and fail to consider alternative explanations. The erratic path to understanding makes interesting reading for anyone with an analytical mind who thinks about the methods of science or the engineering of seeing machines

Discrimination of single bars by the honeybee (Apis mellifera)

AbstractThe bees learn to come for a reward to a very simple pattern, a black bar in a fixed position on a white background, in a Y-choice apparatus, with the targets presented in the vertical plane at a fixed range. They were trained on a number of different arrangements of a single bar on one or both targets. The trained bees were then given appropriate tests to discover what cues they had learned. A cue is an essential parameter that is recognized, not the whole pattern. At the choice point they learn exactly which way to look for consistent cues. After training on a single broad bar versus a blank target, they respond in tests to any area of black where they expect to see it, and are less able to detect it the more it has been displaced from the training position. They are more sensitive to vertical than to horizontal displacement of the bar. The cue is anything black of the right size. They do not recognize the shape or orientation of the bar. When trained to discriminate between two bars at right angles to each other, centred on the reward hole, the cue is the edge orientation at the expected places on the targets, and the bees are less able to discriminate the orientation cues the more they are displaced. When trained on a pair of broad black bars in different positions, the cues are the vertical positions of the centres. Division of the bar into squares, or making the edges stepped, removes the orientation cue but not the position cue. Addition of a large black spot or a checkerboard background to the original bar prevents discrimination, as if the spatial reference frame is disturbed. In training, or testing trained bees, parallax does not assist the discrimination of orientation

Propagation of Power Line Carrier Signals Through the Distribution Transformer.

In the wake of the governments 1989 Electricity act, privatisation reforms have urged the Electricity Supply Industry to enhance the capabilities of its current communication infrastructure . With this realisation , the possibilities of using the industries own distribution network as a communication medium has become a serious proposition. Although this may seem an innovative solution , the use of electrical distribution feeders for conveying information is not in fact new. However, recent advances in technology have provided solutions to the outstanding problem of attaining 'usable' data rates in the harsh power line environment. With this in mind, a power line telecommunications network seems a viable option for the electricity distribution companies. Unfortunately, a system which utilises both LV and MV networks remains presently unattainable , due to the unknown characteristics of the distribution transformer. Having highlighted the need to develop a 'through transformer' signalling system , the frequency characteristics of the distribution transformer have become of paramount interest. Although spread spectrum systems are gaining widespread acceptance, the high process gain required in adverse communication environments mitigates against high data rates. Investigations have demonstrated that an alternative strategy of lower frequency techniques is capable of maintaining a comparable integrity of communications. The following work catalogues the results and draws conclusions from research devoted to an investigation into the propagation of PLC frequency signals through distribution type transformers. From this analysis the viability of a 'through transformer' architecture may be assessed

Would Trade Liberalization Help the Poor of Brazil?

This paper addresses the potential effects of world agricultural trade liberalization on poverty and regional income distribution in Brazil, using an inter-regional applied general equilibrium (AGE) and a micro-simulation model of Brazil tailored for income distribution and poverty analysis by using a detailed representation of households. The model distinguishes 10 different labor types and has 270 different household expenditure patterns. Income can originate from 41 different production activities located in 27 different regions in the country. The AGE model communicates to a micro-simulation model that has around 112,000 Brazilian households and 264,000 adults. Poverty and income distribution indices are computed over the entire sample of households and persons, before and after the policy shocks. The simulated trade liberalization scenario causes agriculture to expand considerably and so, given the importance that agriculture still has for the poorest in Brazil, it has positive impacts on poverty in Brazil. The only states which show an increase in the number of poor households are Sao Paulo and Rio de Janeiro, where the bulk of the manufacturing activities in Brazil are concentrated. There is an even more positive impact on inequality. The higher fall in the poverty gap is shown to occur mainly on the poorest household groups, suggesting that the poorest among Brazil’s poor would benefit more from global trade liberalization.Distorted incentives, agricultural and trade policy reforms, national agricultural development, Agricultural and Food Policy, International Relations/Trade, F13, F14, Q17, Q18,

How bees distinguish colors

Behind each facet of the compound eye, bees have photoreceptors for ultraviolet, green, and blue wavelengths that are excited by sunlight reflected from the surrounding panorama. In experiments that excluded ultraviolet, bees learned to distinguish between black, gray, white, and various colors. To distinguish two targets of differing color, bees detected, learned, and later recognized the strongest preferred inputs, irrespective of which target displayed them. First preference was the position and measure of blue reflected from white or colored areas. They also learned the positions and a measure of the green receptor modulation at vertical edges that displayed the strongest green contrast. Modulation is the receptor response to contrast and was summed over the length of a contrasting vertical edge. This also gave them a measure of angular width between outer vertical edges. Third preference was position and a measure of blue modulation. When they returned for more reward, bees recognized the familiar coincidence of these inputs at that place. They cared nothing for colors, layout of patterns, or direction of contrast, even at black/white edges. The mechanism is a new kind of color vision in which a large-field tonic blue input must coincide in time with small-field phasic modulations caused by scanning vertical edges displaying green or blue contrast. This is the kind of system to expect in medium-lowly vision, as found in insects; the next steps are fresh looks at old observations and quantitative models

Regional Inequality, Poverty and Economic Integration in Brazil.

Gains and losses from trade liberalization are often unevenly distributed inside a country. For example, if budget shares vary according to household income, changes in commodity prices will redistribute an overall welfare change between household types. Household incomes will also be differentially affected. Sectoral differences in factor-intensity mean that changes in industrial structure cause redistribution of income between primary factors. Particular primary factors (such as capital, or less skilled labour) may contribute disproportionately to the incomes of certain household types. The fortunes of such households indirectly depend on the prospects of particular sectors. We emphasize these distributive issues, especially those arising from the income side. At the same time we distinguish households by regions (within the country). The regional distinction sharpens the contrast between groups of households. Particular regions have their own patterns of economic activity and so are differently affected by changes in the industrial protection structure. Since regional household incomes depend closely on value-added from local industries, economic change will tend to redistribute income between regional households. If the regional concentration of poverty is more than we could predict by regional primary factor endowments and industry structure, the addition of a regional dimension will add power to our analysis of income distribution beyond the mere addition of interesting regional detail. The paper deals with these issues more fully. We extend previous regional modeling of Brazil to include the intra-household dimension, addressing poverty and income distribution issues that may be caused by trade integration. An applied general equilibrium (AGE) inter-regional model of Brazil underlies our analysis, with a detailed specification of households. The model is static and solved with GEMPACK. The Representative Household (RH) hypothesis is abandoned; instead a micro-simulation (MS) model is used to track changes in household income and expenditure patterns. This micro-simulation model is built upon two Brazilian household studies: (1) the Household Budget Survey (POF, IBGE, 1999) covers detailed expenditure patterns for 16,013 households and 11 regions in Brazil in 1996; (2) the National Household Sample Survey (PNAD, IBGE, 1997) is a yearly survey that includes detailed information about household employment and income sources, with 331,263 observations. We integrate the two data sources to produce a detailed mapping of expenditure and income sources for 250,000 Brazilian households, distinguishing 50 activities, 80 commodities, and 27 regions. We link the AGE and MS models together, solving them iteratively to get consistency between results. After a shock the AGE model communicates changes in wages and employment by industry and labour type to the MS model that individually simulates the changes in employment, income and expenditure patterns for each household. The new expenditure pattern is then communicated to the AGE model, and the process is repeated until the two models converge. The final results from the MS model enable us to estimate changes in poverty and income distribution measures, both nationally and for regions within Brazil. We use the model to analyze poverty and income distribution impacts of the Free Trade Area of Americas formation upon the Brazilian economy. In the particular simulation we examine, freer trade leads to increased employment, especially for lower-paid workers. Poor households, which contain more enemployed adults, benefit most. This leads to a reduction in poverty in all 27 Brazilian states.

The Doha Round, poverty, and regional inequality in Brazil

This paper addresses the potential effects of the Doha round of trade negotiations on poverty and income distribution in Brazil, using an applied general equilibrium (AGE) and micro-simulation model of Brazil tailored for income distribution and poverty analysis. Of particular importance is the fact that the representative household hypothesis is replaced by a detailed representation of households. The model distinguishes 10 different labor types and has 270 different household expenditure patterns. Income can originate from 41 different production activities (which produce 52 commodities), located in 27 different regions in the country. The AGE model communicates to a micro-simulation model that has 112,055 Brazilian households and 263,938 adults. Poverty and income distribution indices are computed over the entire sample of households and persons, before and after the policy shocks. Model results show that even important trade policy shocks, such as those applied in this study, do not generate dramatic changes in the structure of poverty and income distribution in the Brazilian economy. The simulated effects on poverty and income distribution are positive, but rather small. The benefits are concentrated in the poorest households.Environmental Economics&Policies,Economic Theory&Research,Poverty Assessment,Inequality,Services&Transfers to Poor

Ethanol expansion and indirect land use change in Brazil

In this paper we analyze the Indirect Land Use Change (ILUC) effects of ethanol production expansion in Brazil through the use of an inter-regional, bottom-up, dynamic general equilibrium model calibrated with the 2005 Brazilian I-O table. A new methodology to deal with ILUC effects is developed, using a transition matrix of land uses calibrated with Agricultural Censuses data. Agriculture and land use are modeled separately in each of 15 Brazilian regions with different agricultural mix. This regional detail captures a good deal of the differences in soil, climate and history that cause particular land to be used for particular purposes. Brazilian land area data distinguish three broad types of agricultural land use, Crop, Pasture, and Plantation Forestry. Between one year and the next the model allows land to move between those categories, or for Unused land to convert to one of these three, driven initially by the transition matrix, changing land supply for agriculture between years. The transition matrix shows Markov probabilities that a particular hectare of land used in one year for some use would be in an other use next period. These probabilities are modified endogenously in the model according to the average unit rentals of each land type in each region. A simulation with ethanol expansion scenario is performed for year 2020, in which land supply is allowed to increase only in states located on the agricultural frontier. Results show that the ILUC effects of ethanol expansion are of the order of 0.14 hectare of new land coming from previously unused land for each new hectare of sugar cane. This value is higher than values found in the Brazilian literature. ILUC effects for pastures are around 0.47. Finally, regional differences in sugarcane productivity are found to be important elements in ILUC effects of sugar cane expansion.