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Iowa State University

1. Yin, Anwen. Forecasting and model averaging with structural breaks.

Degree: 2015, Iowa State University

This dissertation consists of three chapters. Collectively they attempt to investigate on how to better forecast a time series variable when there is uncertainty on the stability of model parameters. The first chapter applies the newly developed theory of optimal and robust weights to forecasting the U.S. market equity premium in the presence of structural breaks. The empirical results suggest that parameter instability cannot fully explain the weak forecasting performance of most predictors used in related empirical research. The second chapter introduces a two-stage forecast combination method to forecasting the U.S. market equity premium out-of-sample. In the first stage, for each predictive model, we combine its stable and break cases by using several model averaging methods. Next, we pool all adjusted predictive models together by applying equal weights. The empirical results suggest that this new method can potentially offer substantial predictive gains relative to the simple one-stage overall equal weights method. The third chapter extends model averaging theory under uncertainty regarding structural breaks to the out-of-sample forecast setting, and proposes new predictive model weights based on the leave-one-out cross-validation criterion (CV), as CV is robust to heteroscedasticity and can be applied generally. It provides Monte Carlo and empirical evidence showing that CV weights outperform several competing methods.

Subjects/Keywords: Economics; Forecast Combination; Forecast Evaluation; Forecasting; Model Averaging; Parameter Instability; Time Series; Economics; Finance and Financial Management; Statistics and Probability

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yin, A. (2015). Forecasting and model averaging with structural breaks. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/14720

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yin, Anwen. “Forecasting and model averaging with structural breaks.” 2015. Thesis, Iowa State University. Accessed September 18, 2020. https://lib.dr.iastate.edu/etd/14720.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yin, Anwen. “Forecasting and model averaging with structural breaks.” 2015. Web. 18 Sep 2020.

Vancouver:

Yin A. Forecasting and model averaging with structural breaks. [Internet] [Thesis]. Iowa State University; 2015. [cited 2020 Sep 18]. Available from: https://lib.dr.iastate.edu/etd/14720.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yin A. Forecasting and model averaging with structural breaks. [Thesis]. Iowa State University; 2015. Available from: https://lib.dr.iastate.edu/etd/14720

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Dharmasena, Kalu Arachchillage Senarath. The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation.

Degree: PhD, Agricultural Economics, 2011, Texas A&M University

There are many different types of non-alcoholic beverages (NAB) available in the United States today compared to a decade ago. Additionally, the needs of beverage consumers have evolved over the years centering attention on functionality and health dimensions. These trends in volume of consumption are a testament to the growth in the NAB industry. Our study pertains to ten NAB categories. We developed and employed a unique cross-sectional and time-series data set based on Nielsen Homescan data associated with household purchases of NAB from 1998 through 2003. First, we considered demographic and economic profiling of the consumption of NAB in a two-stage model. Race, region, age and presence of children and gender of household head were the most important factors affecting the choice and level of consumption. Second, we used expectation-prediction success tables, calibration, resolution, the Brier score and the Yates partition of the Brier score to measure the accuracy of predictions generated from qualitative choice models used to model the purchase decision of NAB by U.S. households. The Yates partition of the Brier score outperformed all other measures. Third, we modeled demand interrelationships, dynamics and habits of NAB consumption estimating own-price, cross-price and expenditure elasticities. The Quadratic Almost Ideal Demand System, the synthetic Barten model and the State Adjustment Model were used. Soft drinks were substitutes and fruit juices were complements for most of non-alcoholic beverages. Investigation of a proposed tax on sugar-sweetened beverages revealed the importance of centering attention not only to direct effects but also to indirect effects of taxes on beverage consumption. Finally, we investigated factors affecting nutritional contributions derived from consumption of NAB. Also, we ascertained the impact of the USDA year 2000 Dietary Guidelines for Americans associated with the consumption of NAB. Significant factors affecting caloric and nutrient intake from NAB were price, employment status of household head, region, race, presence of children and the gender of household food manager. Furthermore, we found that USDA nutrition intervention program was successful in reducing caloric and caffeine intake from consumption of NAB. The away-from-home intake of beverages and potential impacts of NAB advertising are not captured in our work. In future work, we plan to address these limitations. Advisors/Committee Members: Capps, Oral (advisor), Bessler, David A. (committee member), Love, Alan H. (committee member), Williams, Gary W. (committee member), Anderson, Richard K. (committee member).

Subjects/Keywords: Non-alcoholic beverages; Heckman Model; Quadratic Almost Ideal Demand System; Houthakker and Taylor model; Barten Synthetic Model; State Adjustment Model; Demand systems; Probability Forecast Evaluation; The Brier Score; Nutritional Contributions of Non-alcoholic beverages; Diversion Ratio; Sugar-sweetened beverages; Yates Partition of the Brier score

…and Demand Systems Study ..................... 2 Probability Forecast Evaluation Study… …Demographic Study and Demand Systems Study ................... 18 Probability Forecast Evaluation… …194 V PROBABILITY FORECAST EVALUATION THROUGH CALIBRATION, RESOLUTION, THE BRIER SCORE AND… …Forecast Evaluation Study .......................................... 84 Qualitative Choice Models… …Rules ............................................................... 88 Probability Forecast… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dharmasena, K. A. S. (2011). The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7911

Chicago Manual of Style (16th Edition):

Dharmasena, Kalu Arachchillage Senarath. “The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation.” 2011. Doctoral Dissertation, Texas A&M University. Accessed September 18, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7911.

MLA Handbook (7th Edition):

Dharmasena, Kalu Arachchillage Senarath. “The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation.” 2011. Web. 18 Sep 2020.

Vancouver:

Dharmasena KAS. The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7911.

Council of Science Editors:

Dharmasena KAS. The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7911

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