Spectral Analysis of Data Generated by Simulation Experiments with Econometric Models

Naylor, Thomas H.; Wertz, Kenneth L.; Wonnacott, Thomas H.

doi:10.2307/1913541

Cited by 41 publications

(14 citation statements)

References 40 publications

(15 reference statements)

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“…Other authors point out that with computational methods, the researchers can avoid oversimplifying the problem [50]. Another point of view is that simulation in social sciences is primarily for exploring poorly understood situations and phenomena as a replacement for an actual (in practice impossible to carry out) experiment [48,[102][103][104]. Such models are obviously closest to hypothesis generators in our above classification.…”

Section: Discussionmentioning

confidence: 99%

Mechanistic models in computational social science

Holme

Liljeros

2015

Front. Phys.

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Quantitative social science is not only about regression analysis or, in general, data inference. Computer simulations of social mechanisms have an over 60 years long history. They have been used for many different purposes-to test scenarios, to test the consistency of descriptive theories (proof-of-concept models), to explore emergent phenomena, for forecasting, etc… In this essay, we sketch these historical developments, the role of mechanistic models in the social sciences and the influences from the natural and formal sciences. We argue that mechanistic computational models form a natural common ground for social and natural sciences, and look forward to possible future information flow across the social-natural divide.

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Section: Discussionmentioning

confidence: 99%

Mechanistic models in computational social science

Holme

Liljeros

2015

Front. Phys.

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“…[26] suggest that the spectra estimated from simulated data be compared with the spectra estimated directly from actual data. There are several ways in which spectrum analytic techniques might be used in the evaluation of econometric models.…”

Section: The Evaluation Of Large Econometric Modelsmentioning

confidence: 99%

Is Verification Possible? The Evaluation of Large Econometric Models

Shapiro

1973

American J Agri Economics

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C ONSTRU CTI ON O.f large econometric models began in earnest during the years of World War II, although some earlier pioneering examples are available. The past two decades, however, mark the period of relatively large and sustained expenditures of energy and resources on the construction of these models. Currently, large econometric models are daily becoming more numerous, more "sophisticated," larger, and certainly more popular. This rising tide of popularity has been temporarily checked from time to time due to the occasional gross forecasting errors generated by these models, but on the whole these "credibility gaps" have been 'short-lived, and the increasing popularity of these devices has flowed on much like GNP and "Ole Man River." Use of large-scale econometric models for forecasting is now widespread in both government and industry; In addition, these models are used by government policy makers for the calculation of policy multipliers, the evaluation of old policies, and for the ranking of prospective new ones. Despite the central importance some of these models have assumed in decision making, the process of systematic model evaluation seems, with some noticeable exceptions, to have received relatively little attention. At the very least the problem of model evaluation has lagged behind the frenetic 250 activity in the area of model construction. Important early work in model evaluation was done by Christ [6], Adelman [1], and Theil [28], among others, and more recently the studies of Zarnowitz, Boschan and Moore [36], Evans, Haitovsky, and Treyz [11], Haitovsky and Wallace [16], as well as the current NSF-NBER Seminar on the Comparison and Evaluation of U. S. Econometric Models [9], [12], and the recent (1969) NBER Conference on Research in Income and Wealth [17], have added considerably to our understanding of this area. Nevertheless it remains true that we still lack a clear and accepted analytical basis for the selection of proper criteria for model evaluation.! Indeed, except for the simplest cases (nested hypothesis) the problem of evaluation and verification of single equation models is far from solved. In this latter area, although there are many more techniques available to aid in the process of model evaluation, there seems to be, among economists, no general agreement on the meaning and purpose of model verification.The purpose of this paper is to help clarify the notion of model verification, particularly in the empirical sciences and suggest how these considerations might "shape" our approach to the problem of the verification of large econometric models. I conclude that it is not possible to consider establishing either the truth or falsity of any theory about the structure of our economic environment, or the models that represent it, and we should instead, turn our attention to the purpose of economic theories 1 This state of affairs was, in part, the motivation for the NBER-NSF seminar on Criteria for Evaluation of Econometric Models. For this seminar's statement of the "state of the a...

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“…The first set of data is derived form USDA in which wholesale prices of Colombian Milds and Brazilian Santos 4 are available over the period January, 1950, to April, 1969 Corporation. The series on coffee prices recorded in the New York market for various brands of coffee are collected from two sources.…”

Section: A Parikh Is a Professor At The University Of East Anglia Nmentioning

confidence: 99%

“…The prices on West African Ambriz are available f'rom January, 1950, to April, 1969. The prices on West African Ambriz are available f'rom January, 1950, to April, 1969.…”

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The Impact of Input Price Inflation on the United States Farming Industry*

Tweeten

Quance

1971

Canadian J Agri Economics

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The "price" ride of the y u~z e in trsditionsllp uttrihuted 10 rapid introduction uf output-increasing technology. which reduces farm industr). income as output p m s n apiinst an inelastic aggregate demand. The care for the price q u~z e has been contested on the one hand by slow intrwuction of output-increasing technolow in the 1960's (evidenced by only 1 nominal gain in U.S. farm productivity) [Cr] and hy the contention that the long-run demand for US. farm output is not price-inelastic [7].' The clasticitin for machincry and buildings are lor mainlenancc. fuel. clc. Elnrticiticr arc no1 included for machincry purcharcr and for building improvements. These latter itcms lend 10 ha\e an clarlic dcmand and are not hipniy productive per dollar spent on them. Hcnce inflation in such tcrms can be cxpcclcd to havc a small impact on aggregate farm costs. rcvcnue. and nct rcvcnue.

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Spectral Analysis of Data Generated by Simulation Experiments with Econometric Models

Cited by 41 publications

References 40 publications

Mechanistic models in computational social science

Mechanistic models in computational social science

Is Verification Possible? The Evaluation of Large Econometric Models

The Impact of Input Price Inflation on the United States Farming Industry*

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