Econometric Models for Probabilistic Choice Among Products

1980 ◽  
Vol 53 (S3) ◽  
pp. S13 ◽  
Author(s):  
Daniel McFadden
Keyword(s):  
Econometric Models ◽  
Probabilistic Choice

Comments on "Econometric Models for Probabilistic Choice Among Products"

1980 ◽  
Vol 53 (S3) ◽  
pp. S31 ◽  
Author(s):  
John Hauser
Keyword(s):  
Econometric Models ◽  
Probabilistic Choice

scholarly journals Econometric Models of Probabilistic Choice: Beyond McFadden’s Formulas

2017 ◽  
pp. 79-87 ◽  
Author(s):  
Olga Kosheleva ◽  
Vladik Kreinovich ◽  
Songsak Sriboonchitta
Keyword(s):  
Econometric Models ◽  
Probabilistic Choice

Comments on "Econometric Models for Probabilistic Choice Among Products"

1980 ◽  
Vol 53 (S3) ◽  
pp. S35 ◽  
Author(s):  
Kenneth M. Gaver
Keyword(s):  
Econometric Models ◽  
Probabilistic Choice

Risk and Volatility: Econometric Models and Financial Practice

CFA Digest ◽  
2005 ◽  
Vol 35 (1) ◽  
pp. 82-83
Author(s):  
Frank T. Magiera
Keyword(s):  
Econometric Models

Current Situation of the Efficiency of the National Budget Allocation in Vietnam

2019 ◽  
Vol 35 (3) ◽  
Author(s):  
Nguyen Trong Vinh ◽  
Nguyen Cam Nhung
Keyword(s):  
Budget Allocation ◽  
Current Situation ◽  
Econometric Models ◽  
The State ◽  
Policy Implications ◽  
State Budget ◽  
National Budget ◽  
Near Future ◽  
Positive Results

This research evaluates the efficiency of the state budget allocation in Vietnam in the period 2007-2016 by using econometric models of OLS, FEM, REM and FGLS. The estimated results from the model, together with the evaluation of the state budget allocation show that the budget allocation has achieved positive results, but the efficiency of budget allocation is still not high. Following this, the article gives some policy implications for Vietnam to effectively allocate the state budget in the near future.

Analysis of the Determinants of International Inbound Tourism Demand: Application of Econometric Models

2018 ◽  
Vol 30 (12) ◽  
pp. 143-159
Author(s):  
Jin-Hee Lee ◽  
Jong-hoon Park ◽  
Kwang-Eik Cho
Keyword(s):  
Econometric Models ◽  
Tourism Demand ◽  
Inbound Tourism

Matrix Powers in Spatial Econometric Models

2014 ◽  
Author(s):  
Sebastian Kripfganz
Keyword(s):  
Econometric Models ◽  
Spatial Econometric ◽  
Spatial Econometric Models

Spatial Effect of Crime on Peer-to-Peer Lodging Performance

2021 ◽  
pp. 004728752110082
Author(s):  
Yu-Hua Xu ◽  
Lori Pennington-Gray ◽  
Jinwon Kim
Keyword(s):  
Peer To Peer ◽  
Spatial Effect ◽  
Econometric Models ◽  
Spatial Econometric ◽  
Community Based ◽  
Negatively Associated ◽  
Business Operations ◽  
Spatial Econometric Models ◽  
Crime Types ◽  
Social Uncertainty

Safety is a major factor impacting consumers’ participation in peer-to-peer (P2P) economies. Using spatial econometric models, this study examined crime effects on the performance (RevPAR) of P2P lodgings at three spatial ranges: property, community, and destination level. The performance of P2P lodgings is negatively associated with crime densities, while the degree of the association varies by crime types and room types. Crime can “spill over” to the neighborhood and have the strongest impact at the community level, followed by the destination level and the property level. The study provides a way to understand tourism risks using criminology theories and the concept of social uncertainty. Empirically, the study provides implications to the governance of community-based lodging business. We suggest that the effect of crime on P2P lodging performance was more conditioned by the safety environment in its neighborhood and the whole destination, rather than individual business operations.

Falsification of Hybrid Systems Using Adaptive Probabilistic Search

2021 ◽  
Vol 31 (3) ◽  
pp. 1-22
Author(s):  
Gidon Ernst ◽  
Sean Sedwards ◽  
Zhenya Zhang ◽  
Ichiro Hasuo
Keyword(s):  
Hybrid Systems ◽  
Input Signal ◽  
Tree Search ◽  
Single Trial ◽  
Decision Point ◽  
Directed Tree ◽  
Probabilistic Choice ◽  
Original Algorithm ◽  
Fine Grained ◽  
Probabilistic Search

We present and analyse an algorithm that quickly finds falsifying inputs for hybrid systems. Our method is based on a probabilistically directed tree search, whose distribution adapts to consider an increasingly fine-grained discretization of the input space. In experiments with standard benchmarks, our algorithm shows comparable or better performance to existing techniques, yet it does not build an explicit model of a system. Instead, at each decision point within a single trial, it makes an uninformed probabilistic choice between simple strategies to extend the input signal by means of exploration or exploitation. Key to our approach is the way input signal space is decomposed into levels, such that coarse segments are more probable than fine segments. We perform experiments to demonstrate how and why our approach works, finding that a fully randomized exploration strategy performs as well as our original algorithm that exploits robustness. We propose this strategy as a new baseline for falsification and conclude that more discriminative benchmarks are required.

Energy consumption flow and econometric models of two plum cultivars productions in Tehran province of Iran

Energy ◽  
2012 ◽  
Vol 44 (1) ◽  
pp. 211-216 ◽  
Author(s):  
Seyed Mohammad Hossein Tabatabaie ◽  
Shahin Rafiee ◽  
Alireza Keyhani
Keyword(s):  
Energy Consumption ◽  
Econometric Models ◽  
Tehran Province
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