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on Computational Economics |
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Issue of 2017‒06‒18
eight papers chosen by |
| By: | Oscar Claveria (AQR-IREA, Universitat de Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain.); Enric Monte (Department of Signal Theory and Communications, Polytechnic University of Catalunya.); Salvador Torra (Riskcenter-IREA, Department of Econometrics, Statistics and Applied Economics, University of Barcelona.) |
| Abstract: | In this study we use agents’ expectations about the state of the economy to generate indicators of economic activity in twenty-six European countries grouped in five regions (Western, Eastern, and Southern Europe, and Baltic and Scandinavian countries). We apply a data-driven procedure based on evolutionary computation to transform survey variables in economic growth rates. In a first step, we design five independent experiments to derive the optimal combination of expectations that best replicates the evolution of economic growth in each region by means of genetic programming, limiting the integration schemes to the main mathematical operations. We then rank survey variables according to their performance in tracking economic activity, finding that agents’ “perception about the overall economy compared to last year” is the survey variable with the highest predictive power. In a second step, we assess the out-of-sample forecast accuracy of the evolved indicators. Although we obtain different results across regions, Austria, Slovakia, Portugal, Lithuania and Sweden are the economies of each region that show the best forecast results. We also find evidence that the forecasting performance of the survey-based indicators improves during periods of higher growth. |
| Keywords: | Economic indicators, Qualitative survey data, Expectations, Symbolic regression, Evolutionary algorithms, Genetic programming.. JEL classification: C51, C55, C63, C83, C93. |
| Date: | 2017–05 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:201711&r=cmp |
| By: | Zura Kakushadze; Willie Yu |
| Abstract: | We provide complete source code for building a fundamental industry classification based on publically available and freely downloadable data. We compare various fundamental industry classifications by running a horserace of short-horizon trading signals (alphas) utilizing open source heterotic risk models (https://ssrn.com/abstract=2600798) built using such industry classifications. Our source code includes various stand-alone and portable modules, e.g., for downloading/parsing web data, etc. |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1706.04210&r=cmp |
| By: | Chuantian He; Chunding Li; John Whalley |
| Abstract: | Transportation costs are an important topic in international trade, but seldom have researches paid attention to general equilibrium trade modelling with transportation costs and explored their relevant effects. This paper uses different numerical general equilibrium trade model structures to simulate the impacts of transportation costs on both welfare and trade for a Canada-US country pair case. We compare two groups of model structure, Armington assumption models and homogeneous goods models. Within these two groups of models, we also compare balanced trade structures to trade imbalance structures, and production function transportation costs to iceberg transportation costs. Armington goods models generate absolute welfare gains from transportation cost elimination than homogeneous goods models. Welfare gains under balanced trade structures are larger in production function transportation cost scenarios, but are larger in iceberg transportation cost scenario under trade imbalance structures. Canada’s welfare gains with iceberg transportation cost are significantly larger than gains with production function transportation cost. On trade effects, homogeneous goods models generate more export and import gains, balanced trade structures have more trade variations, and iceberg transportation cost generate more trade effects. |
| JEL: | F10 F47 O51 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23500&r=cmp |
| By: | ARNOLD, Florian; SÖRENSEN, Kenneth |
| Abstract: | Heuristics are the weapon of choice when it comes to solving complex combinatorial optimization problems. Even though some research focuses on tuning a heuristic with respect to a certain problem, little research has been done to investigate structural characteristics of the problem itself. In this paper we argue that knowledge about a problem is highly valuable when it comes to designing effi cient heuristics, and we show how it can be generated. With knowledge we hereby mean that we can defi?ne desirable structural characteristics of good solutions. Our knowledge generation approach is based on data mining and we demonstrate its concept with the help of the most prominent combinatorial problem in Operations Research, the Vehicle Routing Problem. We de?fine metrics to measure a solution and an instance, and generate and classify 192.000 solutions for various instances. With these metrics we are able to distinguish between optimal and non-optimal solutions with an accuracy of up to 93%. Furthermore, we reveal the most distinguishing characteristics of good VRP solutions, and use them to improve an existing heuristic. |
| Keywords: | Multi-depot vehicle routing problem, Multi-product, Inventory management, Inventory allocation, Metaheuristics |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:ant:wpaper:2017003&r=cmp |
| By: | SeHyoun Ahn; Greg Kaplan; Benjamin Moll; Thomas Winberry; Christian Wolf |
| Abstract: | We develop an efficient and easy-to-use computational method for solving a wide class of general equilibrium heterogeneous agent models with aggregate shocks, together with an open source suite of codes that implement our algorithms in an easy-to-use toolbox. Our method extends standard linearization techniques and is designed to work in cases when inequality matters for the dynamics of macroeconomic aggregates. We present two applications that analyze a two-asset incomplete markets model parameterized to match the distribution of income, wealth, and marginal propensities to consume. First, we show that our model is consistent with two key features of aggregate consumption dynamics that are difficult to match with representative agent models: (i) the sensitivity of aggregate consumption to predictable changes in aggregate income and (ii) the relative smoothness of aggregate consumption. Second, we extend the model to feature capital-skill complementarity and show how factor-specific productivity shocks shape dynamics of income and consumption inequality. |
| JEL: | A0 C0 E0 F0 G0 J0 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23494&r=cmp |
| By: | André De Palma (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Stef Proost (Department of Economics, KU Leuven); Ravi Seshadri (Singapore-MIT Alliance for Research and Technology (SMART) Centre); Moshe Ben-Akiva (MIT - Massachusetts Institute of Technology) |
| Abstract: | To address traffic congestion, two categories of instruments are used: price regulation (for instance, road pricing or congestion tolling) and quantity regulation (credit-based mobility schemes). Although the comparison of price and quantity regulation has received significant attention in the economics community, the literature is relatively sparse in the context of transportation systems. This paper develops a methodology to compare the toll and mobility permit instruments using a simple transportation network consisting of parallel highway routes and a public transport alternative. The permits can be traded across roads. The demand for each route is determined by a mixed logit route choice model and the supply consists of static congestion. The comparison is based on the optimum social welfare which is computed for each instrument by solving a non-convex optimization problem involving the mixed logit equilibrium constraints. Equity considerations are also examined. Numerical experiments conducted across a wide range of demand/supply inputs indicate that the toll and mobility permit instruments perform very closely in efficiency terms. The permit system is on average more efficient, but only by a small margin. |
| Keywords: | Social Welfare, Mixed Logit,Tolls, Mobility Permits, Equity, Stochastic Demand |
| Date: | 2016–11–16 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:hal-01397582&r=cmp |
| By: | Schasfoort, Joeri; Godin, Antoine; Bezemer, Dirk; Caiani, Alessandro; Kinsella, Stephen (Groningen University) |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:gro:rugsom:17010-gem&r=cmp |
| By: | Thomas McGregor |
| Abstract: | The current debate about the optimal management of foreign exchange windfalls is highly relevant to low income countries such as Uganda, having recently discovered vast hydrocarbon reserves. Using a Computable General Equilibrium (CGE) model for Uganda this paper analyses three broad policy options for the use of oil revenues, increasing i) private consumption, ii) private investment, and iii) public infrastructure investment. The model allows for learning-by-doing in tradables, increasing returns to public infrastructure and the use of an Oil Fund held abroad. The fund allows government to smooth expenditure programs over the medium-term. When public infrastructure is biased towards tradables, a smooth expenditure profile yields higher economic growth than high expenditure skewed to the present. The government’s discount rate plays a key role in determining the optimal use and management of oil revenues. More impatient governments will be inclined to increase current expenditure at the cost of future generations’ welfare and negative distributional implications for poor households. Lower discount rates align the political incentives with respect to inter-temporal welfare and the long-run growth path of the economy. |
| Keywords: | Fiscal Policy, natural resources, economic development, Dutch-disease, CGE model, Uganda |
| JEL: | E62 O11 O13 O23 Q32 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:oxf:oxcrwp:186&r=cmp |