DYNAMIC POSITIVE EQUILIBRIUM PROBLEM

The Dynamic Positive Equilibrium Problem (DPEP) is a methodology for dealing with time series about economic agents decisions, regardless of the amount of available information. The approach is articulated in three phases, as in the static counterpart Symmetric Positive Equilibrium Problem (SPEP), with the variant that it must be preceded by the estimation of the equation of motion which characterizes a dynamic model. Furthermore, the definition of marginal cost in the DPEP model is different from the same notion in the static SPEP. In this paper, the DPEP approach was applied to a panel data dealing with annual crops from California agriculture for a horizon of eight years. The dynamic character of the DPEP model is based upon then assumption of output price adaptive expectations that follows a Nerlove-type specification.Research Methods/ Statistical Methods,

A Pairwise Comparison Matrix Framework for Large-Scale Decision Making

abstract: A Pairwise Comparison Matrix (PCM) is used to compute for relative priorities of criteria or alternatives and are integral components of widely applied decision making tools: the Analytic Hierarchy Process (AHP) and its generalized form, the Analytic Network Process (ANP). However, a PCM suffers from several issues limiting its application to large-scale decision problems, specifically: (1) to the curse of dimensionality, that is, a large number of pairwise comparisons need to be elicited from a decision maker (DM), (2) inconsistent and (3) imprecise preferences maybe obtained due to the limited cognitive power of DMs. This dissertation proposes a PCM Framework for Large-Scale Decisions to address these limitations in three phases as follows. The first phase proposes a binary integer program (BIP) to intelligently decompose a PCM into several mutually exclusive subsets using interdependence scores. As a result, the number of pairwise comparisons is reduced and the consistency of the PCM is improved. Since the subsets are disjoint, the most independent pivot element is identified to connect all subsets. This is done to derive the global weights of the elements from the original PCM. The proposed BIP is applied to both AHP and ANP methodologies. However, it is noted that the optimal number of subsets is provided subjectively by the DM and hence is subject to biases and judgement errors. The second phase proposes a trade-off PCM decomposition methodology to decompose a PCM into a number of optimally identified subsets. A BIP is proposed to balance the: (1) time savings by reducing pairwise comparisons, the level of PCM inconsistency, and (2) the accuracy of the weights. The proposed methodology is applied to the AHP to demonstrate its advantages and is compared to established methodologies. In the third phase, a beta distribution is proposed to generalize a wide variety of imprecise pairwise comparison distributions via a method of moments methodology. A Non-Linear Programming model is then developed that calculates PCM element weights which maximizes the preferences of the DM as well as minimizes the inconsistency simultaneously. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology.Dissertation/ThesisPh.D. Industrial Engineering 201

FARM-LEVEL AND MACROECONOMIC DETERMINANTS OF FARM CREDIT MIGRATION RATES

Probit regression techniques are used to identify factors affecting rates of farm credit migration. Macroeconomic factors, such as economic growth signals and money supply increments, increase class upgrade probabilities. Interest rates, a lender's credit rationing and risk management tool, negatively affect such probabilities.Agricultural Finance,

Ordering vs. AHP. Does the intensity used in the decision support techniques compensate?

The manifestation of the intensity in the judgment of one alternative versus another in the peer comparison processes is a central element in some decision support techniques, such as the Analytical Hierarchy Process (AHP). However, its contribution regarding quality (expected performance) with respect to the priority vector has not been evaluated so far. Using the Intentional Bounded Rationality Methodology (IBRM), this work analyzes the gains obtained from requiring the decision-maker to report an intensity judgment in pairs (AHP) with respect to a technique that only requires expressing a preference (Ordering). The results show that when decision-makers have low levels of expertise, it is possible that a less informative and computational cheap technique (Ordering) performs better than a more informative and computational expensive one (AHP). When decision-makers have medium and high levels of expertise, AHP technique obtains modest gains with respect to the Ordering technique. This study proposes a cost-benefit analysis of decision support techniques contrasting the gains of a technique that requires more resources (AHP) against other that require less resources (Ordering). Our results can change the managing approach of the information obtained from experts’ judgments

Ordering vs. AHP. Does the intensity used in the decision support techniques compensate?

The manifestation of the intensity in the judgment of one alternative versus another in the peer comparison processes is a central element in some decision support techniques, such as the Analytical Hierarchy Process (AHP). However, its contribution regarding quality (expected performance) with respect to the priority vector has not been evaluated so far. Using the Intentional Bounded Rationality Methodology (IBRM), this work analyzes the gains obtained from requiring the decision-maker to report an intensity judgment in pairs (AHP) with respect to a technique that only requires expressing a preference (Ordering). The results show that when decision-makers have low levels of expertise, it is possible that a less informative and computational cheap technique (Ordering) performs better than a more informative and computational expensive one (AHP). When decision-makers have medium and high levels of expertise, AHP technique obtains modest gains with respect to the Ordering technique. This study proposes a cost-benefit analysis of decision support techniques contrasting the gains of a technique that requires more resources (AHP) against other that require less resources (Ordering). Our results can change the managing approach of the information obtained from experts’ judgments.Spanish Ministerio de Economía y Competitividad, [ECO2017-86305-C4-3-R]Diputación General de Arag´on (DGA) and the European Social Fund [CREVALOR]CUD (UZCUD2017-SOC-04)Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/https://doi.org/10.13039/501, 100,011,033 and PID2020-113338RB-I0