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on Computational Economics |
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Issue of 2016‒08‒14
nine papers chosen by |
| By: | Ragona, Maddalena; Vitali, Giuliano; Bazzani, Gian Maria |
| Abstract: | This work defines a procedure to assess the socio-economic and environmental sustainability of agricultural systems with a particular attention to conventional and organic farming. Firstly, a mathematical programming model calculates the different multi-dimensional outcomes of Italian farms depending on various levels of prices affecting organic products. Those outcomes are the input data for a fuzzy multi-criteria analysis, which processes the various criteria, takes into account different sets of weights for criteria, and, by a ranking of price scenarios, identifies the most desirable and the least desirable level of prices for five groups of regions. The method adopted proves to be sensitive to geographical location and different perspectives. In particular, when the farmers’ set of weights is adopted, the highest level of prices represents the most desirable scenario in all groups of regions. On the other side, in all other sets of weights, the lowest level of prices seems to be the most preferable scenario for North-Western regions. |
| Keywords: | fuzzy multi-criteria analysis, sustainability assessment, organic farming, conventional farming, analytic hierarchy process, Farm Management, Land Economics/Use, Production Economics, C63, C65, D81, Q12, Q51, |
| Date: | 2016–06–17 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aiea16:242441&r=cmp |
| By: | Michael A. Kouritzin |
| Abstract: | New simulation approaches to evaluating path-dependent options without matrix inversion issues nor Euler bias are evaluated. They employ three main contributions: Stochastic approximation replaces regression in the LSM algorithm; Explicit weak solutions to stochastic differential equations are developed and applied to Heston model simulation; and Importance sampling expands these explicit solutions. The approach complements Heston (1993) and Broadie and Kaya (2006) by handling the case of path-dependence in the option's execution strategy. Numeric comparison against standard Monte Carlo methods demonstrate up to two orders of magnitude speed improvement. The general ideas will extend beyond the important Heston setting. |
| Date: | 2016–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1608.02028&r=cmp |
| By: | Belen Chavez (San Diego Gas & Electric); William Matsuoka (San Diego Gas & Electric) |
| Abstract: | Stata graphics are professional, visually pleasing, and easy to format, but lack the interactive experience or transparency options requested by many users. In this presentation, we introduce a new command, gchart: a fully functional wrapper for the Google Chart API that is written almost entirely like the twoway command, allowing users to write quality JavaScript data visualizations using familiar Stata graphing syntax. While other Google Chart based programs already exist, gchart aims to be the most comprehensive library to-date. With gchart, Stata users can present interactive web-based graphics without exporting their data to secondary software packages or learning JavaScript and HTML. The gchart library contains most Stata graph types such as bar, pie, and line, as well as new graphs offered by Google Charts such as treemaps, timelines, Sankey diagrams, and more! The command contains an option to create interactive tables directly from datasets and even has preset settings to make resulting Google Charts feel more Stata-like. Once the visualizations are rendered, web visitors and/or blog readers will be happy to play with the resulting graphics. |
| Date: | 2016–08–10 |
| URL: | http://d.repec.org/n?u=RePEc:boc:scon16:16&r=cmp |
| By: | Gary Burtless; Anqi Chen; Wenliang Hou; Alicia H. Munnell; Anthony Webb |
| Abstract: | Some observers believe that investing a portion of the Social Security Trust Fund in equities would strengthen its finances and improve the program’s intergenerational risk-sharing. However, equity investments would also expose the program to greater financial risk and potentially greater political risk. Monte-Carlo simulation methods are used to investigate whether equity investments would likely strengthen the long-term outlook of the Trust Fund relative to the current policy of investing 100 percent of reserves in U.S. government bonds. The issues surrounding equity investments also go beyond expected returns on the Trust Fund portfolio. Concerns of government interference with the allocation of capital in the economy and with corporate decision-making as well as the accounting treatment of equity investments are also discussed. |
| Date: | 2016–07 |
| URL: | http://d.repec.org/n?u=RePEc:crr:crrwps:wp2016-6&r=cmp |
| By: | Thomas Masterson; Kijong Kim; Fernando Rios-Avila |
| Abstract: | New methodology for producing employment microsimulations is introduced, with a focus on farms and household nonfarm enterprises. Previous simulations have not dealt with the issue of reduced production in farm and nonfarm household enterprises when household members are placed in paid employment. In this paper, we present a method for addressing the trade-off between paid employment and the farm and nonfarm business activities individuals may already be engaged in. The implementation of the simulations for Ghana and Tanzania is described and the quality of the simulation results is assessed. |
| Keywords: | LIMTCP; Microsimulation; Ghana; Tanzania; Employment; Unpaid Family Labor; Household Production; Time Use |
| JEL: | C14 C40 D31 J22 |
| Date: | 2016–08 |
| URL: | http://d.repec.org/n?u=RePEc:lev:wrkpap:wp_871&r=cmp |
| By: | Prosperi, Maurizio; Lopolito, Antonio |
| Abstract: | Agroenergy, a relatively simple and mature technology to convert biomass into heat and electric energy, may represent a good opportunity to introduce the biorefinery schemes in rural areas. However, to guarantee the feasibility of new investments in this innovative sector, the commitment of all relevant players, and the sharing of their embedded knowledge of local conditions will play a crucial role. In this paper, we propose a modified neural network model to analyse the knowledge extracted from different groups of actors, in order to prevent the definition of strategic plans which may not be not fully consistent. We propose a methodology to support the strategic planning of the agroenergy innovation deployment in rural areas, based on the logical framework of the SWOT analysis, through which the most relevant factors affecting the expectations of local informed actors are identified. Subsequently, a modified multilayered feed-forward neural network is proposed to analyse the qualitative data, in order to verify their consistency. The results obtained from a case study in the province of Foggia (Italy) show that the level of consistency between the perceived factors affecting the deployment of the technology and the expectations towards the successful adoption of agroenergy at local level may vary depending on the degree of involvement and commitment of local players. This may represent a relevant issue for the definition of long-term strategic planning. |
| Keywords: | embedded knowledge, multilayered feed-forward neural networks, SWOT analysis, agroenergy, strategic planning, Agricultural and Food Policy, Research and Development/Tech Change/Emerging Technologies, D83, O32, Q42, |
| Date: | 2016–06–17 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aiea16:242444&r=cmp |
| By: | Ties de Kok (Tilburg University) |
| Abstract: | In my presentation I will give a talk and demonstration on how we can enhance our workflow by using the Jupyter Notebook and my IPyStata package (https://github.com/TiesdeKok/ipystata). IPyStata is a package written in Python that allows users to write and execute Stata and Python code side-by-side in a single Jupyter Notebook. Users can near-seamlessly modify and analyze data using both Stata and Python because IPyStata allows data-structures (e.g. datasets, macros) to be used interchangeably. The Jupyter Notebook (http://jupyter.org) is a phenomenal tool for researchers and data scientists as it allows live code to be combined with explanatory text, equations, visualizations, widgets, and much more. It was originally developed as an open-source tool for interactive Python use (called the IPython Notebook) but is now aimed at being language agnostic under the banner of Project Jupyter. My package, IPyStata, adds Stata to the array of software/programming languages that can be used in the Jupyter Notebook. In my talk I will share how I use Stata, Python, the Jupyter Notebook, and IPyStata to transparently document and share the code and results that underlie my work as an aspiring researcher. For a demonstration notebook see: http://nbviewer.ipython.org/github/Tiesd eKok/ipystata/blob/master/ipystata/Examp le.ipynb |
| Date: | 2016–08–10 |
| URL: | http://d.repec.org/n?u=RePEc:boc:scon16:2&r=cmp |
| By: | Beltran, Daniel O.; Draper, David |
| Abstract: | Central banks have long used dynamic stochastic general equilibrium (DSGE) models, which are typically estimated using Bayesian techniques, to inform key policy decisions. This paper offers an empirical strategy that quantifies the information content of the data relative to that of the prior distribution. Using an off-the-shelf DSGE model applied to quarterly Euro Area data from 1970:3 to 2009:4, we show how Monte Carlo simulations can reveal parameters for which the model's structure obscures identification. By integrating out components of the likelihood function and conducting a Bayesian sensitivity analysis, we uncover parameters that are weakly informed by the data. The weak identification of some key structural parameters in our comparatively simple model should raise a red flag to researchers trying to draw valid inferences from, and to base policy upon, complex large-scale models featuring many parameters. |
| Keywords: | Bayesian estimation ; Econometric modeling ; Kalman filter ; Likelihood ; Local identifcation ; Euro Area ; MCMC ; Policy-relevant parameters ; Prior-versus-posterior comparison ; Sensitivity analysis |
| JEL: | C11 C18 F41 |
| Date: | 2016–08 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1175&r=cmp |
| By: | Billy Buchanan (Office of Research, Evaluation, and Assessment, Minneapolis Public Schools) |
| Abstract: | Exploratory data analysis/visualization is the bedrock upon which we construct our understanding of the world around us. It is an immensely powerful tool for developing our understanding of the data and to communicate our results in ways that are intuitive to many audiences. As our data increases in its complexity, static visualizations may not be the most efficient or sufficient method to extract the same meaning from the data. The jsonio, libd3, and libhtml packages were developed specifically to address this limitation within Stata and to provide a toolkit upon which other users could easily and quickly contribute. The jsonio package is a Java plugin that helps users to generate JSON objects from the data they have in Stata, and unlike .csv also retains crucial metadata that can help interpret the meaning of the data visualizations (e.g., value labels, variable labels, etc…). The libd3 Mata library mimics the D3js API as closely as possible to make it easier for users to take existing code and implement it in Mata without significant effort. The libhtml library provides HTML5 DOM element classes for constructing HTML documents. Together, these form a powerful toolkit for interactive exploratory data analysis and visualization. |
| Date: | 2016–08–10 |
| URL: | http://d.repec.org/n?u=RePEc:boc:scon16:3&r=cmp |