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on Computational Economics |
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Issue of 2017‒04‒09
twenty papers chosen by |
| By: | Elena Ianchovichina; Shantayanan Devarajan; Csilla Lakatos |
| Abstract: | This paper quantifies the global economic effects and strategic responses to the lifting of economic sanctions on Iran. The proposed lifting of sanctions, following its July 14, 2015 nuclear agreement with the permanent members of the UN Security Council and Germany (“P5+1”), will have consequences for the global, regional, and Iranian economies. The global effects will be felt mostly through the oil channel. The resumption of Iranian oil exports to pre-2012 levels could eventually add one million barrels per day on the world oil market, bidding down world prices. There will also be regional effects on Iran’s major trading partners, including the United Arab Emirates and other countries in the Middle East and Central Asia, through an expansion of oil and non-oil trade, as sanctions-induced trading costs come down. Finally, there will be effects on Iran’s economy as barriers to trade are relaxed, the production mix shifts in favor of goods that fetch high prices abroad and its consumption towards cheaper imports, with attendant effects on economic growth, efficiency and household welfare. This paper quantifies the economic effects of the lifting of sanctions on Iran using a modified version of the GTAP 9 database (Narayanan et al., 2015) and a global, computable general-equilibrium (CGE) model, GTAP, documented in Hertel (1997). CGE models capture the interaction between producers and consumers in the economy, mediated through the price mechanism. The global CGE model also captures the trade flows between countries and solves for a set of world prices that equilibrate global supply and demand. We use the model to simulate the effect of a “shock”, such as the removal of a trade embargo, on the market-clearing prices at the global and national levels. We are therefore able to isolate the consequences of the lifting of sanctions from other ongoing developments in the economy. Since the model captures the new equilibrium of an economy that has been perturbed, the time horizon of a simulation is best thought of as medium term, i.e. three to five years. In our simulations, the lifting of economic sanctions on Iran has three components. The first is the lifting of the EU oil embargo. The 2012 restrictions on imports of Iranian oil by the EU were the most far-reaching of the sanctions as they curtailed the volume of exports of Iran’s most important export commodity. Thus, the removal of the EU oil embargo is expected to have the largest macroeconomic impact on Iran and the rest of the world as oil accounts for about 64 percent of Iranian export revenue and Iran has a relatively large share (8 percent) of total world exports. The second component is the removal or significant reduction of the cargo inspections on Iranian exports and imports that were imposed as part of the sanctions regime. Transport costs on trade with Iran are expected to decline. This in turn will have an effect on Iran’s merchandise trade and boost in particular exports and imports of bulky goods and other goods with large transport margins, such as agricultural and industrial products and machinery. The third component is associated with improvements in non-tariff barriers affecting Iran’s cross-border imports of financial and transport services. As the US and other partners lift restrictions on financial transactions and transport services, Iran’s imports of these services are expected to rise. Simulations with the model show that gains from the embargo removal are the largest for Iran, resulting in a welfare gain of about $18 billion to the economy, or an increase in per capita welfare of 3.7 percent. Almost half of these gains (1.7 percent or approximately $8.2 billion) stem from the lifting of the EU oil embargo, while the reduction in trade costs and improvements in conditions for cross-border services trade result in additional gains of $2.0 billion and $7.5 billion, respectively. The gains to Iran will be 22 percent lower if Iran’s oil exports to the EU do not recover completely but reach only half of their pre-sanction levels. This may be a more likely outcome since a full bounce back may not be possible in the medium term due to various impediments to oil production and exports, including a range of technical constraints on crude oil extraction and high domestic oil demand, to name a few. In the global economy, net oil importers gain and net oil exporters lose as the world price of oil declines by about 13 percent due to the additional amount of oil sold on the global market. The gains to the EU and the US, both net oil importers, are sizable in absolute terms $67 billion and $34 billion but small in relative terms as per capita welfare increases by slightly less than a half of a percent in the EU and a quarter of a percent in the US. The losses are steepest for OPEC members, especially the GCC, which are expected to lose 3.9 percent in per capita welfare (equivalent to $55 billion in 2011 prices). Per capita welfare for other OPEC members and Russia declines by 2.9 percent ($19 billion) and 1.6 percent ($30 billion), respectively. The rest of the world is not significantly affected by the reduction in Iran’s trade costs because Iran is responsible for a negligible share of the world’s non-oil exports. Overall, the removal of Iran’s economic sanction translates into a gain for the world economy of $53 billion. Iran gains the most in per capita terms, while the losses of oil exporting countries are large and of similar absolute magnitude to Iran’s gains. The paper also considers the strategic responses of different trading blocks to the lifting of the sanctions. Major oil exporters may limit their own oil output and exports in order to stabilize world oil prices. We assess the effect of such a strategic move in combination with the lifting of Iran’s sanctions. Recognizing that Iran’s policy responses will have a substantial effect on the country’s ability to benefit from the lifting of sanctions, we consider the effects of two policy reforms: (i) unilateral reduction of tariffs on imported capital goods and (ii) reforms intended to boost automobile production. Finally, we assess the effects of improved market access for Iranian exports in western markets in response to credible signs of successful implementation of the nuclear agreement. We find that if major OPEC members limit the quantity of oil produced and exported in order to leave the world price of oil unchanged, the global welfare gains from the removal of the EU oil embargo would be significantly reduced. Compared to the baseline scenario, world-wide welfare gains decrease by 70 percent, from $54 billion to $16 billion. Iran’s welfare gains are enhanced and the losses to oil exporting countries reduced, but not by enough to compensate for the oil importers’ reduced welfare gains. The benefits to Iran will also increase if the lifting of the embargo is accompanied with national economic reforms that strengthen the supply response. With a reduction of tariffs on imports of capital goods, welfare gains are expected to be $1.8 billion larger for Iran than in the baseline scenario. Policies that encourage the expansion of automobile production to pre-sanction levels would translate into even higher gains. Given the importance of this industry to the Iranian economy, these reforms translate into a 40 percent boost to welfare or $7 billion. Exports of automobiles are found to increase by more than two-fold benefiting all factors of production but most significantly the returns to capital and skilled labor. Finally, improved market access to the west benefits not only Iran, but also the market-access-granting countries. The supply response will be stronger and the welfare effects larger if investment in general, and foreign direct investment in particular, picks up. |
| Keywords: | Iran, EU, US, Russia, Israel, GCC OPEC, Other MENA, Other OPEC, Rest of World, Impact and scenario analysis, Trade issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9185&r=cmp |
| By: | Dirk Willenbockel; Claudia Ringler; Nikos Perez; Mark Rosegrant; Tingiu Zhu; Nathanial Matthews |
| Abstract: | There is a growing recognition that the ambitious UN Sustainable Development Goals (SDG) to end hunger, achieve food security and promote sustainable agriculture (SDG 2), to ensure universal access to water and sanitation (SDG 6), to ensure universal access to affordable, reliable, sustainable and modern energy (SDG7) and to combat climate change and its impacts (SDG 13) are linked in complex ways. The emerging literature on the energy-water-food nexus highlights the need to take account of the trade-offs and synergies among the goals arising from these linkages, but also underscores the need for further research to understand the quantitative relevance of the various channels through which measures towards the attainment of the goals affect each other. The presence of multiple conceivable pathways to the achievement of the SDGs by 2030 as well as the numerous uncertainties surrounding medium- to long-run projections for the global food system call for a scenario approach to development policy planning, and the development of plausible scenarios needs to be informed by quantitative modelling that captures the key linkages between energy, water, food and climate policy in a stylized form. Dynamic standard global computable general equilibrium (CGE) models are able to capture the input-output linkages between agricultural, food processing and energy sectors and the impacts of population and economic growth on structural change, energy and food demand as well as the impacts of policy interventions, but due to their coarse regional aggregation structure they are not suitable to take account of physical water scarcity constraints in a persuasive manner. In contrast, existing partial equilibrium (PE) multi-market models of global agriculture can incorporate hydrological constraints at detailed regional scales and support a more disaggregated representation of agricultural commodities than CGE models, but fail to take systematic account of linkages between agriculture, energy and the rest of the economy. To capture the advantages of both modelling approaches, the present study links a global dynamic multisector CGE model with a global dynamic PE multi-market model of agricultural supply, demand and trade. The linked modelling framework facilitates a quantitative analysis of the wider implications of agricultural sector scenario projections by taking systematic account of linkages between agriculture and the rest of the economy and allows a rigorous theory-grounded general equilibrium welfare analysis of shocks to agriculture. Conversely, the linked approach supports a detailed analysis of the effects of shocks that initially hit non-agricultural sectors on agricultural variables and water security. In this paper, the approach is used to assess the impact of stylised climate change mitigation scenarios on energy prices, economic growth, food security and water availability. The modeling methodology links the global computable general equilibrium (CGE) model GLOBE-Energy with IFPRI’s International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) version 3. IMPACT3 is a modular integrated assessment model, linking information from climate models, crop simulation models and water models to a global partial equilibrium multi-market model of the agriculture sector. IMPACT3 has been designed to support longer-term scenario analysis through the integration of these multidisciplinary modules to provide researchers and policymakers with a flexible tool to assess and compare the potential effects of changes in biophysical systems, socioeconomic trends, agricultural technologies, and policies. The core multimarket model simulates food supply and demand for 159 countries. Agricultural production is further disaggregated to include 320 food production units (FPUs), which are intersections of river basins and national boundaries, that is, an intersection of 154 river basins with 159 economic regions. The multimarket model simulates 62 agricultural commodity markets, covering all key food as well as key non-food crops, such as cotton. The water models in IMPACT3 include a global hydrology model (IGHM) that simulates snow accumulation and melt and rainfall-runoff processes at 0.5-degree latitude by 0.5-degree longitude resolution, a water basin supply and demand model (IWSM) that operates at the FPU level, and the IMPACT crop water allocation and stress model that estimates the impact of water shortages on crop yields, also at the FPU level. These three modules allow for an assessment of climate variability and change on water availability for the agriculture and other sectors, as well as for an assessment of changes in water demand, investment in water storage and irrigation infrastructure, and technological improvements on water and food security. In particular, the IGHM model simulates natural hydrological processes, thus estimating water availability, while the IWSM model simulates human appropriation of surface water and groundwater, considering water infrastructure capacity and policies, based on which we water stress calculations. The model can also simulate impact of changes in fertilizer prices on food supply and changes in energy prices on the demand for hydropower development and on groundwater pumping. GLOBE-Energy is a recursive-dynamic multi-region CGE model which features a detailed representation of the technical substitution possibilities in the power sector. The model is initially calibrated to the GTAP 8.1 database which represents the global economy-wide structure of production, demand and international trade at a regionally and sectorally disaggregated level for the benchmark year 2007. The model version employed in the present study distinguishes 24 commodity groups and production sectors, and 15 geographical regions. In the development of a dynamic baseline for the present study, the growth rates of labor-augmenting technical progress by region are calibrated such that the regional baseline GDP growth rates replicate the GDP growth assumed in the IMPACT baseline projections. Moreover, for agricultural commodities, the sectoral total factor productivity parameters are calibrated such that the baseline producer price paths are consistent with the corresponding aggregated IMPACT producer price projections. To ensure that the baseline projections for agricultural quantity variables generated by GLOBE are broadly in line with the corresponding aggregated IMPACT projections as well, the parameters of the household consumer demand system are calibrated to be consistent with the aggregated household income elasticities of demand for the matched food commodity groups assumed in IMPACT. The aggregate real income effects and changes in fertilier prices associated with energy-related climate change mitigation measures generated by GLOBE are then downscaled to the IMPACT regional aggregation level and passed back to IMPACT to analyse the detailed implications for agricultural variables, water and food security. The simulation analysis compares a baseline scenario using SSP2 (Shared Socio-Economic Pathway 2 – aka “middle of the road”) assumptions about population and GDP growth and no changes in fossil fuel taxes, with a stylized mitigation scenario. This mitigation scenario assumes a gradual linear phasing-in of additional taxes on the use of primary fossil fuels globally from 2016 onwards up to 2050 on top of baseline taxes such that the additional ad valorem tax wedges between producer and user prices reach 70, 50 and 30 percent for coal, crude oil and natural gas respectively by 2050. The resulting user price increases for the primary fossil fuels and refined petrol induce substitution effects towards renewable energy sources in production along with investments in more energy-efficient technologies as well as substitution effects towards less energy-intensive goods in final consumption. As a consequence, the demand for fossil fuels drops relative to the baseline and the producer prices for coal, crude oil and natural gas fall significantly, while the producer prices of refined petrol rise due to the increase in crude oil input costs. From a macroeconomic perspective, these price shifts entail terms-of-trade gains for regions that are net importers of the primary fossil fuels and corresponding terms-of-trade losses for the net importers of these fuels. Correspondingly, the aggregate real income reductions under this scenario are moderate to small for the net importing regions but more pronounced for the net exporters of primary fossil fuels. The provisional simulation results suggest only moderate indirect effects on agricultural prices and food security outcomes. While higher prices for chemical fertilizers and reduced groundwater pumping due to higher energy costs per se push crop prices up to some extent, the adverse real income effect on food demand pull crop prices in the opposite direction. The price effects are slightly more pronounced when the energy price increases are assumed to induce a significant increase in first-generation biofuel production relative to IMPACT baseline assumptions. |
| Keywords: | Global multi-region , Impact and scenario analysis, General equilibrium modeling |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9746&r=cmp |
| By: | Roberto Roson |
| Abstract: | This paper presents an external module for the Python programming language and for the SAGE open source mathematical software, which allows the realization of models based on constrained optimization or non-linear systems. The module, which is freely available for download, allows describing the structure of a model using a syntax similar to that of popular modeling systems like GAMS, AIMMS or GEMPACK; in particular by allowing the automatic replication of equations, variable and parameter definitions on the basis of some specified sets. Many applied models, especially in economics, are based on non-linear constrained optimization and system solving. Years ago, the standard way to realize simulations for this kind of models involved writing your own code, using a programming language like FORTRAN, possibly making calls to external math library subroutines. Subsequently, the introduction of packages like Matlab, GAUSS, Octave and many others have made this process somewhat simpler, because vectors and matrices could be treated as single variables, and complex numerical tasks could be performed with a single instruction. However, one fundamental problem remained: the model code still looked much different from the more familiar mathematical notation one would have used in a paper. Therefore, checking and modifying the model code written by another researcher was a rather daunting task. To address this issue, GAMS (General Algebraic Modeling System) was developed by Alexander Meeraus and many of his collaborators at the World Bank in Washington D.C., since the late '70s (Meeraus, 1983). The main purpose of GAMS was (and still is) “providing a high-level language for the compact representation of large and complex models” and “permitting model descriptions that are independent of solution algorithms”. This paper presents an external module for the Python programming language and for the SAGE open source mathematical software, based on the same principles underlying GAMS and other similar packages. The purpose is providing a tool that takes the best of both worlds: the simplicity and clarity of GAMS-like systems combined with the flexibility and power of Python and SAGE. The paper is structured as follows. In the next section, some key characteristics of GAMS and other popular Modeling Systems are reviewed in some detail. Section 3 introduces the Python programming language and the closely related SAGE system for symbolic and numerical computation. Section 4 illustrates the basics of the PAMS.py syntax, and in Section 5 a practical example is provided. A discussion follows in Section 6 and a final section concludes. The paper presents an external module for programs written with the Python language and for the SAGE mathematical software. This module allows the definition and solution of non-linear systems and optimization problems, described in a way very similar to GAMS and programs alike. The key common characteristic of PAMS.py and GAMS is the automatic indexing of parameters, equations and variables. Since many elements of this kind can be defined with only one instruction (as one would normally do, for instance when the model is illustrated in a scientific paper), understanding how the model works directly by reading the program code is normally quite straightforward. The latter feature turns out to be particularly critical when the model code needs to be understood and manipulated by others, which may occur either in a team work or when replication and validation of some results is called for. |
| Keywords: | None, Modeling: new developments, Miscellaneous |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9165&r=cmp |
| By: | Francesco Lamperti; Andrea Roventini; Amir Sani |
| Abstract: | Taking agent-based models (ABM) closer to the data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs combining supervised machine-learning and intelligent sampling to build a surrogate meta-model. The proposed approach provides a fast and accurate approximation of model behaviour, dramatically reducing computation time. In that, our machine-learning surrogate facilitates large scale explorations of the parameter-space, while providing a powerful filter to gain insights into the complex functioning of agent-based models. The algorithm introduced in this paper merges model simulation and output analysis into a surrogate meta-model, which substantially ease ABM calibration. We successfully apply our approach to the Brock and Hommes (1998) asset pricing model and to the ``Island'' endogenous growth model (Fagiolo and Dosi, 2003). Performance is evaluated against a relatively large out-of-sample set of parameter combinations, while employing different user-defined statistical tests for output analysis. The results demonstrate the capacity of machine learning surrogates to facilitate fast and precise exploration of agent-based models' behaviour over their often rugged parameter spaces. |
| Keywords: | agent based model; calibration; machine learning; surrogate; meta-model |
| Date: | 2017–03–04 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2017/11&r=cmp |
| By: | Lorenza Campagnolo; Fabio Eboli; Marinella Davide |
| Abstract: | The fall of 2015 will see a redefinition of international policy environment with the 21th UNFCCC Conference Of Parties (COP 21) in Paris and the adoption of the Sustainable Development Goals (SDGs) by United Nations. SDGs, the Millennium Development Goals follow-up, will set broader and more ambitious targets for both developed and developing countries encompassing all sustainability dimensions (economic, social, and environmental) and designing the pathway towards an inclusive green growth. The COP 21 agreement, defining new emission targets (Intended Nationally Determined Contributions - INDCs), will directly affect countries’ environmental performance, but also social and economic dimensions if we consider the possible use of climate policy revenues to reduce poverty prevalence (SDG 1) and malnutrition (SDG 2) or to extend access to electricity (SDG 7) or to lower the pressure on public debt (SDG 8). This paper aims at giving an ex-ante assessment of the co-benefits and side effects of this new policy setting and, in particular, to shed some light on the influence of COP21 agreement on achieving SDGs. Our analysis relies on a recursive-dynamic Computable General Equilibrium (CGE) model developed and enriched with indicators representative of each SDGs. CGE models have a flexible structure, and can capture trade‐offs and higher-order implications across sectors and countries that follows a shock or a policy. These models are well suited to assess the performance of economic indicators such as sectoral value added, GDP per capita, and public debt evolution; moreover, the CGE modelling literature of the past decades has highlighted that this is also a powerful tool to assess the evolution of some key environmental indicators, such as land use determined by land owners’ revenues maximisation or GHG and CO2 emissions directly linked to agents’ production and consumption choices (Böhringer and Löschel, 2006). Modelling social indicators in a CGE framework is a difficult task, especially when these imply dispersion measures such are poverty prevalence and inequality at the core of GOAL 1 and 10. In this case, we overcome the representative agent structure proper of CGE models empirically relying on the empirical literature and directly estimating the relations between indicators and endogenous variables of the model (Bourguignon et al., 2005; Ferreira et al., 2007; Montalvo and Ravallion, 2010). Extending the model with social and environmental indicators, in addition to the economic ones, allows assessing in an internally consistent framework how and at which extent changes in one sustainability sphere may affect the achievement of SDGs all around the world. Our framework considers 33 indicators covering 16 SDGs and classified into the three sustainability pillars. The analysis has world coverage, but for modelling reasons we aggregate the result in 40 countries/macro-regions. The historical records of indicators’ values rely on international databases (Commission on Sustainable Development of the United Nations, EU Sustainable Development Strategy, and World Development Indicators from World Bank) and are the starting point in our baseline scenario design. The baseline reproduces a Shared Socio-economic Pathways 2 (SSP2), consistent with a RCP4.5, and it is used as a benchmark to assess the effects of two mitigation scenarios anticipating the outcome of COP 21. The two proposed mitigation scenarios consider a coordinated effort to curb GHG emissions from 2020: 1.Post-Paris Global Trade (global ITS) scenario: the abatement pledges stated in the INDCs submitted ahead of the Paris Conference (COP 21) are effective for the committing countries. The global climate policy implementation envisions an international emission trading scheme (ITS). 2.Post Paris EU ETS scenario: in this scenario the European Union (EU28) implements an Emission Trading System (ETS) as already foreseen by the EU ETS domestic legislation, while all other countries achieve their targets unilaterally with a domestic carbon tax. Both scenarios are characterised by two different recycling schemes of the revenues collected from the carbon market or the carbon taxes: •revenues are redistributed internally in a lump sum; •revenues are used in part internally in EU28 and other developed countries and in part flow to a Development Fund benefiting LDCs: EU28 uses at least 50% of the revenues recycled to support clean energy in EU, 5% goes to the Development Fund and the rest is redistributed internally. The other committing countries allocate 1% of the carbon tax revenues to the Development Fund. In the LDCs revenues are recycled to achieve other SDGs, e.g. poverty and malnutrition reduction, access to education and electricity. This analysis will mainly focus on characterising the future trend of some social indicators, e.g. poverty prevalence and inequality, in the SSP2 baseline scenario, in addition to the usual economic and environmental indicators. Then, this baseline scenario will be used as a term of comparison to assess the impact of climate policy and different recycling scheme on environmental, social and economic indicators. Considering the INDCs as binding targets, COP21 agreement will determine a slight reduction of extreme poverty prevalence in the LDCs, but this outcome is mainly due to a leakage effect. The effect of climate policy on income distribution will be neutral and recycling carbon revenues with the creation of a Development Fund and a lump sum transfer to LDCs will have a negligible effect on poverty and inequality. |
| Keywords: | Global, but with a focus on LDCs, General equilibrium modeling, Developing countries |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9635&r=cmp |
| By: | Johanes Agbahey; Khalid Siddig; Harald Grethe |
| Abstract: | The Palestinian-Israeli conflict witnessed a new development in the mid-90s with the introduction of the closure policy. This policy consisting in roadblocks, and fixed and mobile checkpoints restricts the movement of goods and labor between the Palestinian territories and Israel, between the West Bank and the Gaza Strip, and inside the West Bank. As a result of this policy the economic space of the West Bank is divided into small pieces and trade with the rest of the world is distorted. The impact of the closure policy on the West Bank's economy is largely understudied. Taking advantage of this unique context, this study addresses the economy-wide effects of removing the closures. The study uses a SAM developed for the West Bank for the year 2011 with explicit representation of trade and transport margins. A variant of the STAGE suite of CGE models is used and extended to conform the unique feature of the West Bank economy. In this paper the removal of the closures is simulated through the reduction of the trade and transport margins by 30%, and the increase in efficiency in the transportation sector by 30%. The results suggest that removing the closure policy will induce a substantial growth of the West Bank's economy by 2 to 7% and will have distributional effects among the household groups Model and data The model used in this study belongs to the STAGE suite of CGE models. STAGE-2 uses a combination of linear and non-linear relationships governing the behavior of the model’s agents (Mc-Donald and Thierfelder, 2013). The model explicitly accounts for transport and trade margins and allows to capture the transactions costs associated with the closure regime that is investigated in this study. The model is calibrated to a West Bank SAM for 2011 (Agbahey et al., forthcoming). The full SAM comprises 325 accounts, of which 83 are commodities and 49 are activities. This detailed disaggregation allows assessing the impact of the closure regime on trade for specific commodity groups and the multiplier effects on the production sectors. The SAM also includes three margin accounts, namely wholesale trade, retail trade and transport margins. The depiction of the margins in the SAM is essential to study the effects of the closure regime as the restrictions basically increase the transaction costs. The SAM encompasses 59 production factor accounts and 111 household groups, allowing the assessment of the multiplier effects on factor markets and households’ welfare. Finally, the SAM singles out Israel from the rest of the world allowing to capture explicitly the transactions between Israel and the West Bank. Simulations The closure regime has two major effects on trade in the West Bank. First, it raises transaction costs. Passage at checkpoints and uncertainty of closures generate delays and add to the costs of doing business. The second major impact is on productivity in the transportation sector. The back-to-back system in place requires trucks upon arrival at a checkpoint to be unloaded and then reloaded on to another truck. This system causes additional labour and fuel costs and a decline in the factor productivity in the transportation sector. Three simulations are run in this study. The first simulates a reduction in the transaction costs associated with the closures. Akkaya et al. (2008) estimated the closure-induced increase in transaction costs at about 33%. In this first simulation, a pre-closure situation is reproduced by removing 33% of the transport and trade margins. In the second simulation factor productivity in the transportation sector is increased. In the absence of a documented estimation of the decline in productivity in the transportation sector, a 33% increase is assumed. Finally, the third simulation combines the first two. Sensitivity analysis is conducted to assess the extent to which the results are robust to differences in the magnitude of the imposed shock. Reduced transaction costs and increased productivity in the transportation sector would potentially have strong effects on the West Bank economy. Total domestic production is expected to increase, as the economy benefits from better access to import markets for intermediate inputs and higher export revenues. The effects between sectors, however, may differ strongly and some sectors may suffer from stronger import competition and changes in factor prices. Higher production would on average have positive multiplier effects on labour income and ultimately on household income. Effects on different household groups will differ according to their composition of income as well as consumption expenditure. However, for the economy as a whole, welfare gains are expected to largely offset losses. |
| Keywords: | West Bank (Palestine), General equilibrium modeling, Impact and scenario analysis |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9197&r=cmp |
| By: | Colasante, Annarita; Alfarano, Simone; Camacho Cuena, Eva; Gallegati, Mauro |
| Abstract: | In this paper, we elicit both short and long-run expectations about the evolution of the price of a financial asset by conducting a Learning-to-Forecast Experiment (LtFE) in which subjects, in each period, forecast the the asset price for each one of the remaining periods. The aim of this paper is twofold: on the one hand, we try to fill the gap in the experimental literature of LtFEs where great effort has been made in investigating short-run expectations, i.e. one step-ahead predictions, while there are no contributions that elicit long-run expectations. On the other hand, we propose an alternative computational approach with respect to the Heuristic Switching Model (HSM), to replicate the main experimental results. The alternative learning algorithm, called Exploration-Exploitation Algorithm (EEA), is based on the idea that agents anchor their expectations around the past market price, rather than on the fundamental value, with a range proportional to the recent past observed price volatility. Both algorithms perform well in describing the dynamics of short-run expectations and the market price. EEA, additionally, provides a fairly good description of long-run expectations. |
| Keywords: | Expectations, Experiment, Evolutionary Learning |
| JEL: | C91 D03 G12 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:77618&r=cmp |
| By: | Kleijnen, J.P.C. (Tilburg University, Center For Economic Research) |
| Abstract: | This tutorial reviews the design and analysis of simulation experiments. These experiments may have various goals: validation, prediction, sensitivity analysis, optimization (possibly robust), and risk or uncertainty analysis. These goals may be realized through metamodels. Two types of metamodels are the focus of this tutorial: (i) low-order polynomial regression, and (ii) Kriging or Gaussian processes). The type of metamodel guides the design of the experiment; this design .…xes the input combinations of the simulation model. However, before a regression or Kriging metamodel is applied, the many inputs of the underlying realistic simulation model should be screened; the tutorial focuses on sequential bifurcation. Optimization of the simulated system may use either a sequence of low-order polynomials— known as response surface methodology— or Kriging models .…tted through sequential designs. Finally, "robust" optimization should account for uncertainty in simulation inputs. The tutorial includes references to earlier WSC papers. |
| Keywords: | regression; Kriging; Gaussian process; factor screening; optimization; risk analysis |
| JEL: | C0 C1 C9 C15 C44 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiucen:c7ad6b68-dcd6-4485-9ee2-08d2e3eab6cb&r=cmp |
| By: | Gioele Figus; Patrizio Lecca; Karen Turner; Peter McGregor |
| Abstract: | Energy rebound effect from increased energy efficiency has been generally considered as an undesired consequence of increasing energy efficiency policies that needs to be accounted when assessing the ability of such policies to decrease the demand for energy. However, recent studies have associated the energy rebound effect to a wider range of economic benefits coming from the higher energy efficiency. In computable general equilibrium (CGE) setting Lecca et al. 2014 show that a more efficient use of energy could lead to a reallocation of household’s expenditure towards non-energy sectors, which could stimulate the economy through a shift in the aggregate demand. However this would crowd out export due to an increased pressure on domestic consumption price. Here we use a regional (CGE) model for the Scottish economy to analyse the economic response of household - and of the wider economy - to an increase in household energy efficiency. We follow the approach of Lecca et al. 2014 but we focus on the regional case of Scotland. This allows us to understand some of the implications of moving from a national to a regional CGE modelling framework in the analysis of the impacts household energy efficiency improvements in the whole economy. The macroeconomic impacts of improving household energy efficiency are analysed using a CGE model for Scotland called AMOS-ENVI. This is a dynamic CGE model with forward-looking investment and consumption decisions, designed to analyse environmental and energy disturbances in a regional setting. The model accounts for 20 different productive sectors, including 4 supply chain energy industries, and includes information about fScottish households, the Scottish Government and imports and exports to the rest of the UK (RUK) and to the rest of the World (ROW). Wages are determined within the region in an imperfectly competition setting, using a wage curve where the real wage is negatively related to unemployment rate. The labour force is initially assumed fixed. We than release this assumption to allow for free workers interregional migration across UK, occurring in response to the difference between national and regional real wage and unemployment rates. We consider an energy efficiency improvement as being any technological change which allows households to consume the same bundle goods as before but using less physical energy in doing this. The rebound effect is measured as being the ratio between potential energy savings (PES) and actual energy savings (AES). The PES correspond to the pure engineering effect, for example improving efficiency by 10% and saving 10% of energy. The AES are calculated as the proportionate change in a specific energy use, for which efficiency has improved, as the result of the full general equilibrium adjustments. Results from simulations show that increasing household energy efficiency stimulates the Scottish economy through an increase and change in patterns in the domestic aggregate demand. In the long-run central case scenario the regional GDP increases by 0.11%, unemployment rate drops by 0.45% and households consumption increases by 0.4%. The consumption of energy decreases both in household and in production, although the calculated general equilibrium rebound effect is 50%, so that only 50% of the potential energy savings are achieved. By introducing free migrations of workers, we find that in an open region characterised by an integrated labour market, interregional migration of workers may give additional momentum to the economic expansion from the increased household energy efficiency. In fact the net in-migration relieves pressure on the real wage and the cpi, which return to their baseline values in the long-run restoring the lost competitiveness observed in the national case (Lecca et al., 2014). By considering different simulation scenarios we show that there is a friction between the economic expansion from increased household energy efficiency and the rebound effects. Moreover, we show that the economic stimulus from increased energy efficiency in household would be different depending on the precise specification of the impact itself. |
| Keywords: | Scotland, General equilibrium modeling, Energy and environmental policy |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9454&r=cmp |
| By: | Jonathan Pycroft; María Teresa Álvarez-Martinez; Salvador Barrios; Maria Gesualdo; Dimitris Pontikakis |
| Abstract: | Corporate tax reforms in the EU are motivated by evidence that the current system is unfair and inefficient. Uncoordinated national tax regimes can feature tax loopholes and inconsistencies in the treatment of corporate profits across borders that give rise to strategic tax planning by multinational corporations. There is growing recognition of these issues and a renewed impetus to address them. Attempts to improve international coordination of national corporate tax policies are being undertaken through the OECD Base Erosion and Profit Shifting (BEPS) Project. In this paper, we evaluate the effects that changing the corporate income tax (CIT) rate may have on EU countries using a Computable General Equilibrium (CGE) model. The model captures the key features of the corporate tax regimes including investment decisions, loss compensation, multinational profit shifting and the debt-equity choice of firms. This is a multi-regional model including all 28 EU member states, the USA and Japan. It encapsulates the behaviour of all economic agents, reflecting both the direct and indirect effects of policy changes on macroeconomic variables, such as GDP, investment and employment. We simulate the impact of removing differences in corporate tax rates across EU countries and their effect on tax competition considering both uncoordinated and coordinated changes. For each of the three simulations, revenue neutrality is maintained by adjusting labour taxes to compensate for any revenue increase or shortfall caused. In addition, sensitivity analysis is performed, ensuring budget neutrality through adjusting transfer to pensioners or government expenditure. We first consider simulations where one country raises or lowers its rate in isolation. We simulate an upward adjustment in a low CIT tax economy, namely Ireland, up to the level of a higher tax economy, namely Germany. These two countries represent to polar examples since Ireland has the lowest statutory CIT rate in the EU and in Germany, which is the largest country in the Union, the CIT rate is among the highest. Second, we simulate the reverse case, where Germany reduces its rate to the Irish level. In each case, we observe the impact on the country affected as well as the international spillover effects. The third simulation supposes that all EU member states choose to harmonise their CIT rates at the EU average level. The first two simulations reveal that a tax shift from labour tax to corporate tax (Ireland) has a negative impact on GDP, whilst a tax shift from corporate tax to labour tax (Germany) has a positive impact on GDP. On the other hand, the impact on (after-tax) wages moves in the opposite direction. As anticipated, the German CIT rate simulation causes larger spillover effects, with all other countries' GDP being negatively affected to some degree. Nevertheless, the benefits to Germany are sufficient to slightly raise EU GDP by 0.19 percent. The third simulation, where CIT rates are harmonised across the EU, tends to suggest that a tax shift from corporate tax to labour tax raises GDP, whilst the opposite tax shift lowers GDP; this holds true for 22 out of 28 EU countries. The aggregate impact is a small fall in EU GDP of 0.13 percent. This result broadly holds for the alternative budget-neutral closures. A benefit of CIT rate harmonisation is that it removes much of the incentive to engage in profit shifting. We conclude that reforming corporate taxes can generate substantial responses within the implementing country as well as beyond its own borders. Harmonisation of CIT rates would likely involve winners and losers, and as such, may be best pursued gradually and as part of a broader package of corporate tax reform. |
| Keywords: | European Union, Tax policy, General equilibrium modeling |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9324&r=cmp |
| By: | Yeongjun Yeo; Yeongjun Yeo; SHIN, Ki-yoon; Jeong-Dong Lee |
| Abstract: | Nowadays, with increasing interests of demand-side innovation policy, there is needs for investigating public procurement policy aiming to strengthen the industrial competitiveness by expanding new markets with innovative activities. Public Procurement is regarded as the most effective policy for stimulating innovation in relevant sectors. Under this background, each countries in OECD spends about 15~20% of its GDP on public procurement, and most of the demands in industry and technology sector such as energy, environment, health, construction is stimulated by public procurement. Especially, in order to achieve both mitigating climate change and economic revitalization, the share of green public procurement which is public procurement for green products in total public procurement is enlarging among developed countries. Despite of the amount of public procurement, and policy significance and effectiveness, there is few study on the effects of public procurement for innovation and the macroeconomic analysis from public procurement. In addition, some empirical studies which investigated policy impact of green public procurement are also limited in partial equilibrium perspectives, and they did not show the integrated and macro-economic impact of public procurement. Therefore, with previous literature reviews, this study presents general equilibrium perspectives which can analyze environmental, economic, and social benefits from public procurement simultaneously. Based on the conceptual framework from the previous literature, this study will present empirical results of the impacts of green public procurement quantitatively by computable general equilibrium(CGE) model. To analyze the economic impacts of green public procurement, it is essential to represent the innovation activities and its contributions within the CGE model. For the analysis, we construct the knowledge-based social accounting matrix(SAM), which includes knowledge in factors of production and R&D investment under investment. In addition, we construct the knowledge-based CGE model to capture the innovation related activities, and its effects on the macroeconomic system. Main differences between the knowledge-based CGE model and conventional CGE model is that factors of production include knowledge, and investment includes R&D investment. Another difference is that industry-specific knowledge stock accumulated by R&D investment influences productivity of other industries through spillover effect. These features of knowledge-based CGE model enable us to understand various macro-economic effects of green public procurement(GPP) considering innovation related aspects. Although green public procurement(GPP) could have indirect and direct effects on the economy in terms of environmental, economic, and social perspectives, previous literature give us bounded information in understanding potential effects of the GPP. This is because most studies on the GPP are limited to a specific cases based on the theoretical or conceptual level, and analyzing its effect with partial equilibrium perspectives. Firstly, GPP can have environmental impacts through energy savings and reduction of greenhouse gases by reducing energy consumption with the procurement of energy efficient products by the public sectors. Each country including Korea has its own standards of energy efficiency for the products, and GPP is implemented as the government preferentially buy the products with high levels of energy efficiency. Secondly, the GPP can have economic impacts through creating and escalating the market, because the public sector take a role of lead consumer in green products and services. As a lead consumer, the public sector reduce market and technological uncertainties by specification of the demand of green technology and products. Thanks to the public sector, potential suppliers can escalate their pre-commercialization R&D and commercialization process. That is, GPP reduce the uncertainty across whole stage of production from development of new technology to diffusion of the products by specifying the information on demand for the industry, and it leads more innovation activity of suppliers and investment for the production. Therefore, this study aims to analyze the various impacts of green public procurement in environmental, and economic perspectives as discussed above. In addition, GPP’s main effects could appear in various pathways, including the environmental, economic, and social factors. Therefore, as an empirical study we will try to model those factors within the knolwedge-based CGE model. |
| Keywords: | South Korea, General equilibrium modeling, Impact and scenario analysis |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9519&r=cmp |
| By: | Tesfatsion, Leigh |
| Abstract: | Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these properties imply real-world economies are locally-constructive sequential games. This study discusses a modeling approach, agent-based computational economics (ACE), that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented. The remainder of the study then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing. |
| Date: | 2017–03–28 |
| URL: | http://d.repec.org/n?u=RePEc:isu:genstf:201703280700001022&r=cmp |
| By: | Motaz Khorshid; Saad Nassar; Victor Shaker |
| Abstract: | Permitted under the Article (XXIV) of GATT/WTO, Free Trade Agreements (FTAs) have become a prominent feature in the current trading system. Its share in total world trade has increased tremendously. Although it may be considered an easy substitute for a more difficult multilateral arrangement, it goes further beyond what is agreed upon in the world trade organization. In this regard, FTAs may provide lessons and suggest good practices that could be used to enhance economic policy debate. The current research is directed to assess and quantify the economy wide consequences of the proposed FTA between Egypt and the United States, which represents an important stepping stone towards a regional free trade agreement with the countries of the Middle East and North Africa (MENA) following the bottom-up approach in negotiation. Unlike the previous studies, which are mainly based on qualitative analysis, partial equilibrium or general equilibrium static models, the present research develops a dynamic computable general equilibrium (CGE) model that captures the interaction between the agriculture sector and the rest of the economy in a consistent and comprehensive manner. As an analytical tool, the model – as well as its social accounting matrix- reflects three technical modifications to the CGE modeling tradition. First, it represents an issue- oriented economy-wide modeling approach that establishes the linkages between agriculture sector and the rest of the economy. Second, it handles the case of multiple rest of the world with similar exchange rate and different regions (USA and the rest of the world). Third, aggregate investment spending is broken down into investment of domestic origin and foreign direct investment (FDI) flows. Given the above economic rationale, the model is used to capture and assess the impact of two main effects: (i) the effect of removing tariffs on trade between Egypt and the United States, which is nominated the "shallow agreement effect " and (ii) the effect generated by the shallow agreement in addition to reducing non-tariff measures and increasing FDI inflows from the United states, which is nominated the " the deep agreement effect". Taking into account the scheduled total annual U.S. aid to Egypt, the main results of the simulation experiments can be summarized as follows: First, the main results show that the aggregate and sectoral impacts in all experiments are quite modest due to the fact that the bilateral trade and investment flows with the United States are relatively small. Second, reducing non-tariff measures and attracting U.S. Foreign direct investment flows as part of the deep agreement is expected to provide positive gains in the medium/long run with an increase in average annual growth rate of real gross domestic product (GDP) accounting for 1.87% compared with the reference path. Third, Analytical results show limited structural changes caused by the deep agreement in the medium-long run. Fourth, the experimental analysis shows a clear improvement in Egypt’s external balance. This improvement is apparent in exports, trade balance and the current account surplus. Sixth, the deep agreement is expected to have positive effects on real households consumption and Investment as well as terms of trade and employment. However, it shows a negative effect on aggregate national saving. |
| Keywords: | Egypt, General equilibrium modeling, Agricultural issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9243&r=cmp |
| By: | MUHAMMAD RIFQI; YOSHIO KANAZAKI |
| Abstract: | We attempt to develop and evaluate financial distress prediction models using financial ratios derived from financial statements of companies in Indonesian manufacturing industry. The samples are manufacturing companies listed in Indonesian Stock Exchange during 2003-2011. The models employ two kinds of methods : traditional statistical modeling (Logistic Regression and Discriminant Analysis) and modern modeling tool (Neural Network). We evaluate 23 financial ratios (that measure a company's liquidity, profitability, leverage, and cash position) and are able to identify a set of ratios that significantly contribute to financial distress condition of the companies in sample group. By utilizing those ratios, prediction models are developed and evaluated based on accuracy and error rates to determine the best model. The result shows that the ratios identified by logistic regression and the model built on that basis is more appropriate than those derived from discriminant analysis. The research also shows that although the best performing prediction model is a neural network model, but we have no solid proof of neural network's absolute superiority over traditional modeling methods. |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:toh:dssraa:62&r=cmp |
| By: | Amirhossein Sobhani; Mariyan Milev |
| Abstract: | In this Article, a fast numerical numerical algorithm for pricing discrete double barrier option is presented. According to Black-Scholes model, the price of option in each monitoring date can be evaluated by a recursive formula upon the heat equation solution. These recursive solutions are approximated by using Legendre multiwavelets as orthonormal basis functions and expressed in operational matrix form. The most important feature of this method is that its CPU time is nearly invariant when monitoring dates increase. Besides, the rate of convergence of presented algorithm was obtained. The numerical results verify the validity and efficiency of the numerical method. |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1703.09129&r=cmp |
| By: | Isono, Ikumo; Kumagai, Satoru |
| Abstract: | We use a geographical simulation model to assess the economic impacts of special economic zones (SEZs) and other policy measures in Myanmar. We compare cases wherein SEZ development is concentrated in Thilawa/Yangon with those wherein it is dispersed among 15 districts. We find that concentrated development has a much larger economic impact on Myanmar. Moreover, this impact is larger when we assume the development of a domestic economic corridor and regulatory reform in addition to the development of Thilawa and may reduce the excessive inflow of households into the Yangon area. We also discuss how delaying the dispersion of development affects the economic impacts on Yangon and other regions as well as on Myanmar. |
| Keywords: | Special economic zone, Economic development, Economic geography, Simulation, New economic geography, Myanmar, Special economic zone |
| JEL: | O53 R12 R13 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:jet:dpaper:dpaper639&r=cmp |
| By: | Marek Radvansky; Miroslav Stefanik |
| Abstract: | In this paper we build on an already developed labour market model (VZAM) (Tiruneh, 2012), (Lubyova, Stefanik et al., 2015), designed to project skill shortages on Slovak labour market. Within the model several relatively autonomous modules work on the supply and demand side. Existing approaches in modelling labour market development in terms of skills, differentiate between expansion demand and replacement demand for labour (CEDEFOP, Skills supply and demand in Europe, 2009, 2010 and 2011). Replacement demand captures the demand arising from transitions and implied job openings. Transitions considered are those between segments (sector/occupation) as well as into unemployment and various forms of inactivity (retirement, schooling, maternity leave and other). Replacement demand usually presents a major part of the demand created in each labour market (Kriechel and Sauermann, 2010), (Kriechel, 2013). Similar approach has been also applied in Slovakia (Radvansky, Miklosovic and Hvozdikova, 2016). The objective of the submitted paper is to explore the possibilities of switching the module on replacement demand from a semi aggregate probability model into microsimulation framework. For this purpose open-source microsimulation software LIAM 2 will be employed (http://liam2.plan.be/). Switching into a micro-simulation form could be related to several advantages in comparison to a simple probability model. It would, for example, allow us to consider individuals´ history in the probability functions on transitions and thus improving the quality of predictions. The functionality of LIAM 2 also allows us to consider more and multiple stage processes, relevant from the perspective of individual decision. The objective of the paper is to explore and consider the advantages related to switching an already existing replacement module (based on age specific simple probability functions) into a microsimulation framework. Outputs will be compared to previously obtained methods and their reliability will be discussed. The demand side of the VZAM model follows this distinction between expansion and replacement demand. Expansion demand is modelled using a dynamic CGE model (Miklosovic and Radvansky, 2015). This is complemented with a methodologically different module on replacement demand. In this module, age specific probability functions are used in order to predict transitions into retirement and outside the labour force. The objective of this paper is to switch the module on replacement demand into a micro simulation framework, in order to predict transitions between segments of the labour market (sectors/occupations), into unemployment and out of the labour force. Aggregate outputs from this module are consequently produced and imported into other modules of the VZAM model. The supply side of VZAM predicts detailed structure of the educational structure of the Slovak population combining LFS, Census and administrative data on schooling participants. The replacement module also imports aggregate information, such as the one about relative wage in segments, as well as the educational structure from other modules of the model. Within the replacement module, individual data from the Labour Force Survey (LFS) are processed and complemented with more precise information from national administrative data. In the paper we will focus purely on the outputs from the replacement module, but we will keep existing functional interlinkages with other parts of the model. The results obtained by the new (micro simulation) version of the replacement module will be extracted in a form comparable to the previous applications. Basic indicators of flows and transitions into retirement, other forms of inactivity, unemployment as well as into other segments of the labour market will be extracted. These will be produced by sector of economic activity, age group and educational level. Predictions from the new version of the module will be confronted with results from the previous version and especially the fit with real LFS microdata will be considered (with respect to LFS sample related shortcomings). The most recent (2015) round of LFS will be considered in order to assess the nowcasting potential of the designed approach. |
| Keywords: | Slovakia, applicable to all countries in CEE region, Microsimulation models, Labor market issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9541&r=cmp |
| By: | Yeongjun Yeo; Sungmoon Jung; Jeong-Dong Lee; Won-Sik Hwang; Yeongjun Yeo |
| Abstract: | In the 1990s and the early part of the 2000s, many countries in the world have gone through the ‘jobless growth’ in which employment stalled while economy grew. In many countries since the global financial crisis, there has also been occasions where the unemployment rate has increased instead of falling although the economy has bounced back. Likewise, South Korea has been going through this ‘jobless growth’ since the middle of the 2000s. There are various claims in the circles of economics as to the cause of such phenomenon, one of which is that it’s due to technological innovation. That is, as technologies progress, productivity and output increases, but the demand for jobs decreases and has a bad influence on employment. Particularly, in the case of South Korea, which has reached the highest degree of intensity in its investment in R&D as continuous investment therein has increased, points are being raised that this is the cause of the ‘jobless growth’. Not only the quantitative aspect of employment but also the qualitative aspect is an issue, and, while technological innovation increases the demand for skilled laborers, it stunts the demand for unskilled laborers. That is, it brings about skill-biased technology change. Especially, Brynjolfsson and McAfee (2014) claimed in their book ‘The Second Machine Age’ that, as information communication technology advances, new technologies and machines replace jobs faster, technological innovation causes skill-biased technology change and capital-biased technology change, and leads to income polarization. However, the recently raised arguments are only considering the direct influences that innovation has on employment.Therefore, the influence of innovation on employment and growth should be examined with its indirect effects as well as direct. Hence, in this study, using the computable general equilibrium model, which is capable of concurrently considering various aspects of economy, it was intended to examine what influence innovation has on employment structure and economic growth. The innovation affects employment through various routes. Especially, when diversity of products increases through innovation, it leads to indirect influences in which new demand is created and the employment increases. Therefore, the influence of innovation on employment and growth should be examined with its indirect effects as well as direct. Hence, in this study, using the computable general equilibrium model, which is capable of concurrently considering various aspects of economy, it was intended to examine what influence innovation has on employment structure and economic growth. For this, knowledge-based Social Accounting Matrix and knowledge-based computable general equilibrium model have been constructed. The result of the study utilizing the knowledge-based computable general equilibrium model is summed up as follows. Viewed from the employment aspect first, additional innovative activities turned out to increase the total demand of labor, increasing the demand for unskilled, skilled, and high-skilled labor all together. The demand for the high-skilled labor especially showed the highest increase rate. When examined by the industry, the high-tech manufacturing which invests heavily in R&D also showed the greatest rate of employment increase. In sequence, when viewed from the aspect of economic growth, additional innovative activities turned out to have a positive influence on economic growth, which led to the increase in all production elements’ added values. In the case of capital, high-skilled labor, and knowledge, however, while their weights in added values have increased, unskilled and skilled labors’ weights in added value turned out to have decreased by the capital-biased technology change and the skill-biased technology change. Accordingly, the foregoing turned out to have a bad influence on income distribution and deepened income polarization. Meanwhile, when viewed by the industry, due to the additional innovative activities, the output of the manufacturing industry turned out to show a higher increase rate than that of the service industry. |
| Keywords: | South Korea, General equilibrium modeling, Labor market issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9524&r=cmp |
| By: | Allen, D.E.; McAleer, M.J.; Singh, A.K. |
| Abstract: | This paper features a tri-criteria analysis of Eurekahedge fund data strategy index data. We use nine Eurekahedge equally weighted main strategy indices for the portfolio analysis. The tri-criteria analysis features three objectives: return, risk and dispersion of risk objectives in a Multi-Criteria Optimisation (MCO) portfolio analysis. We vary the MCO return and risk targets and contrast the results with four more standard portfolio optimisation criteria, namely the tangency portfolio (MSR), the most diversifed portfolio (MDP), the global minimum variance portfolio (GMW), and portfolios based on minimising expected shortfall (ERC). Backtests of the chosen portfolios for this hedge fund data set indicate that the use of MCO is accompanied by uncertainty about the a priori choice of optimal parameter settings for the decision criteria. The empirical results do not appear to outperform more standard bi-criteria portfolio analyses in the backtests undertaken on our hedge fund index data. |
| Keywords: | Keywords: MCO, Portfolio Analysis, Hedge Fund Strategies, Multi-Criteria Optimisation, Genetic Algorithms. |
| JEL: | G15 G17 G32 C58 D53 |
| Date: | 2016–12–30 |
| URL: | http://d.repec.org/n?u=RePEc:ems:eureir:98658&r=cmp |
| By: | Adeola Oyenubi |
| Abstract: | This paper provides a plausible explanation for why the optimum number of stocks in a portfolio is elusive, and suggests a way to determine this optimal number. Diversification is dependent on the number of stocks in a portfolio and the correlation structure. Adding stocks to a portfolio increases the level of diversification, and consequently leads to risk reduction. However the risk reduction effect dissipates after a certain number of stocks, beyond which additional stocks do not contribute to risk reduction. To explain this phenomenon, this paper investigates the relationship between portfolio diversification and concentration using a genetic algorithm.To quantify diversification, we use the Portfolio Diversification Index (PDI). In the case of concentration, we introduce a new quantification method. Concentration is quantified as complexity of the correlation matrix. The proposed method quantifies the level of dependency (or redundancy) between stocks in a portfolio. By contrasting the two methods it is shown that the optimal number of stocks that optimizes diversification depends on both number of stocks and average correlation. Our result shows that, for a given universe, there is a set of Pareto optimal portfolios each containing a different number of stocks that simultaneously maximizes diversification and minimizes concentration. The preferred portfolio among the Pareto set will depend on the preference of the investor. Our result also suggests that an ideal condition for the optimal number of stocks is when the variance reduction as a result of adding a stock is off-set by the the variance contribution of complexity. |
| Keywords: | Information Theory, Diversification, Genetic Algorithm, Portfolio optimization, Principal Component Analysis, Simulation methods, Maximum Diversification Index |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:rza:wpaper:666&r=cmp |