In this paper a nonstatistical framework for assessing behaviorally based policy models is presented. Such a framework is needed because statistical criteria do not explicitly indicate how well various aspects of a disaggregated model fit together. The framework assumes models have five elements: behavior specificity, motivation or goal specificity, decision-heuristic specificity, belief specificity, and exogenous variable specificity. After the elements have been defined, three models are assessed using the framework. It is found that the framework works well across diverse models but requires considerable refinement and empirical verification.
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References
1.
AjzenIFishbeinM, 1980Understanding Attitudes and Predicting Social Behavior (Prentice-Hall, Englewood Cliffs, NJ).
2.
AmemiyaT, 1979, “The estimation of a simultaneous tobit model”International Economic Review20169–181.
3.
AnasAChuC, 1984, “Discrete choice models and the housing price and travel to work elasticities of location demand”Journal of Urban Economics15107–123.
4.
BeckerG, 1965, “A theory of the allocation of time”Economic Journal75493–517.
5.
BerryLTonnB, 1984, “Loan impacts in home energy audit programs: A Minnesota example” ORNL/CON-145, Oak Ridge National Laboratory, Oak Ridge, TN.
6.
BosherJSchweppeFGruhlJ, 1978, “Validity and uncertainty of predictive energy models” in Proceedings of the Sixth Power Systems Computation Conference Darmstadt, West Germany (IPC Science and Technology Press, Guildford, Surrey) pp 93–99.
7.
BoulierBRosenzweigM, 1984, “Schooling, search and spouse selection: Testing economic theories of marriage and household behavior”Journal of Political Economy92712–732.
8.
BrownM AMaceyS M, 1983, “Understanding residential energy conservation through attitudes and beliefs”Environment and Planning A15405–416.
9.
DammDLermanS, 1981, “A theory of activity scheduling behavior”Environment and Planning A13703–718.
10.
DubinJMcFaddenD, 1984, “An econometric analysis of residential electric appliance holdings and consumption”Econometrica52345–362.
11.
GAO, 1979, “Guidelines for model evaluation” PAD-79-17, US General Accounting Office, Washington, DC.
12.
GassS, 1983, “Decision-aiding models: Validation, assessment, and related issues for policy analysis”Operations Research31603–631.
13.
HamblinD, 1985, “Documentation of the Oak Ridge National Laboratory residential reference house energy demand model”Oak Ridge National Laboratory, Oak Ridge, TN.
14.
HanemannW M, 1984, “Discrete/continuous models of consumer demand”Econometrica52541–562.
15.
HausmanJ, 1980, “Validation and assessment procedures for energy models” in Validation and Assessment of Energy Models Ed. GassS, Special Publication 79–86 (National Bureau of Standards, Washington, DC) pp 79–86.
16.
HollowayM (Ed.), 1980Texas National Energy Modeling Project: An Experiment in Large-Scale Model Transfer and Evaluation (Academic Press, New York).
17.
ICF, Inc. and Mathematical Policy Research, 1981, “Analysis of conservation improvements and retrofits changes in the residential sector”prepared for the Energy Information Administration, US Department of Energy; copy obtainable from ICF Inc., Washington, DC.
18.
JacksonJLamnR, 1983, “Development of fuel choice and floor space models for BPAs commerical moder Economic Development Laboratory, Georgia Institute of Technology, Atlanta, GA.
19.
KahnemanDTverskyA, 1979, “Prospect theory: An analysis of decision under risk”Econometrica47263–291.
20.
KeenP, 1977, “The evolving concept of optimality” in Multiple Criteria Decision Making Eds StarrMZelenyM (North-Holland, New York) pp 31–58.
21.
KentR, 1984, “Housing tenure choice: Evidence from time series”Journal of Urban Economics15195–209.
22.
KieferN, 1984, “Microeconomic evidence on the neoclassical model of demand”Journal of Econometrics25185–302.
23.
KrummR, 1982, “Household demand for home heating”Resources and Energy4121–144.
24.
LancasterK, 1971Consumer Demand: A New Approach (Columbia University Press, New York).
25.
LehrerE, 1983, “Determinants of child care mode choice: An economic perspective”Social Science Research1269–80.
26.
LehrerENerloveM, 1984, “The impact of expected child survival on husbands' and wives' desired fertility in Malaysia: A log-linear probability model”Social Science Research13236–249.
27.
LongleyP A, 1984, “Comparing discrete choice models: Some housing market examples” in London Papers in Regional Science 14. Discrete Choice Models in Regional Science Ed. PitfieldD (Pion, London) pp 163–180.
28.
ManskiCMcFaddenD (Eds), 1981Structural Analysis of Discrete Data with Econometric Applications (MIT Press, Cambridge, MA).
29.
MaslowA, 1970Motivation and Personality (Harper and Row, New York).
30.
MillerGGalanterGPribramK, 1960Plans and the Structure of Behavior (Holt, Rinehart, and Winston, New York).
31.
NCSO, 1974, “Philippines 1970 Census of Population and Housing”National Census and Statistics Office, Manila.
32.
PasE I, 1984, “The effect of selected sociodemographic characteristics on daily travel-activity behavior”Environment and Planning A16571–581.
33.
PoliakRWachterM, 1975, “The relevance of the household production function and its implication for the allocation of time”Journal of Political Economy83255–277.
34.
SellR, 1983, “Analyzing migration decisions: The first step—whose decisions”Demography20299–311.
35.
SimonH, 1976Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization (Free Press, New York).
36.
SimonH, 1979, “Rational decision making in business organizations”American Economic Review69493–513.
37.
SteinbrunnerJ, 1974The Cybernetic Theory of Decision (Princeton University Press, Princeton, NJ).
38.
StolzenbergRWaiteL, 1984, “Local labor markets, children and labor force participation of wives”Demography21157–170.
39.
ThobaniM, 1984, “A nested logit model of travel mode to work and auto ownership”Journal of Urban Economics15287–301.
40.
ThomsonE, 1983, “Individual and couple utility of children”Demography20507–518.
41.
ThornberryTChristensenR, 1984, “Unemployment and criminal involvement: An investigation of reciprocal causal structures”American Sociological Review49398–411.
42.
TimmermansH J P, 1984, “Discrete choice models versus decompositional multiattribute preference models: A comparative analysis of model performance in the context of spatial shopping-behaviour” in London Papers in Regional Science 14. Discrete Choice Models in Regional Science Ed. PitfieldD (Pion, London) pp 88–101.
43.
TonnB E, 1984a, “A sociopsychological contribution to the theory of individual time-allocation”Environment and Planning A16201–223.
44.
TonnB E, 1984b, “The cyclic process decision-heuristic: An application in time-allocation modeling”Environment and Planning A161197–1220.
45.
TonnB EBerryL, 1984, “Conservation potentials, participation, and retrofit choices in the Connecticut Residential Conservation Service (CONN SAVE) Program” ORNL/CON-161, Oak Ridge National Laboratory, Oak Ridge, TN.
46.
WeisbinCPeelleRLoeblA, 1981, “An approach to evaluating energy-economy models” ORNL/TM-5742, Oak Ridge National Laboratory, Oak Ridge, TN.
47.
WoodD, 1980, “Model assessment and the policy research process: Current practice and future promise” in Validation and Assessment Issues of Energy Models Ed. GassS, Special Publication 564 (National Bureau of Standards, Washington, DC) pp 23–62.
48.
WrigleyN, 1982, “Quantitative methods: Developments in discrete choice modeling”Progress in Human Geography6547–562.
49.
WrigleyNDunnR, 1984, “Stochastic panel-data models of urban shopping behaviour: 3. The interaction of store choice and brand choice”Environment and Planning A161221–1236.
