Computational economics by David A. Kendrick

By David A. Kendrick

The power to conceptualize an monetary challenge verbally, to formulate it as a mathematical version, after which signify the math in software program in order that the version may be solved on a working laptop or computer is a vital ability for economists. Computational Economics comprises famous models--and a few brand-new ones--designed to assist scholars circulate from verbal to mathematical to computational representations in monetary modeling. The authors' concentration, even though, isn't just on fixing the types, but in addition on constructing the facility to switch them to mirror one's curiosity and perspective. the result's a publication that allows scholars to be artistic in constructing versions which are suitable to the industrial difficulties in their instances. in contrast to different computational economics textbooks, this publication is equipped round financial subject matters, between them macroeconomics, microeconomics, and finance. The authors hire numerous software program systems--including MATLAB, Mathematica, GAMS, the nonlinear programming solver in Excel, and the database platforms in Access--to let scholars to take advantage of the main constructive approach. The ebook progresses from quite uncomplicated versions to extra advanced ones, and contains appendices at the fine details of operating each one program.The booklet is meant to be used via complicated undergraduates economists or even, as a primary publicity to computational economics, via graduate scholars. prepared by way of monetary subject matters Progresses from easy to extra advanced versions comprises directions on a variety of software program structures Encourages customization and creativity

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001 and increase the number of iterations. Probably the most important element in the Solver Options Dialog Box is Use Automatic Scaling. In many neural net data sets the various series may be of very different magnitudes. 04 and a consumption series with numbers like 625. In such a case it is wise to check the automatic scaling option. If you do this, the Solver will automatically scale all of your series so that they are roughly of the same magnitude and thereby increase the probability that the Solver will be able to find an optimal set of parameter estimates.

Check the column at2 and you will find that it is similar to the column at1 except that it uses data from the input data for x4 and x5 to compute the second of the two hidden layer values. Consider next the Output Layer column. It is computed using an expression of the form Output = theta0 + theta1 * at1 + theta2 * at2 where the thetas are weights which are computed in the optimization and that are shown in the section on Output weights near the top of the spreadsheet. Next look at the Error column in the Data Set section of the spreadsheet.

31 Chapter 2 Neural Nets in Excel Much of economics is about finding optimal variables given parameters which describe human behavior. For example in the optimal growth model that we solved with Excel the goal was to find the optimal levels of the consumption and capital stock variables given the parameters of the production function and the utility function. In this chapter we invert this duality. We begin with the observed behavior and attempt to find the parameters which permit the specified relationships to most closely fit the data.

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