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on Discrete Choice Models |
| By: | Ian Crawford (Institute for Fiscal Studies and University of Oxford); Matthew Polisson (Institute for Fiscal Studies and University of Leicester) |
| Abstract: | This paper presents a nonparametric analysis of a common class of intertemporal models of consumer choice that relax consumption independence. Within this class and in the absence of any functional form restrictions on instantaneous preferences, we compare the revealed preference conditions for rational habit formation and rational anticipation. We show that these models are nonparametrically equivalent in the presence of finite date sets composed of prices, interest rates, and consumption choices. |
| Keywords: | anticipation, habits, revealed preference, time separability |
| JEL: | D11 D12 D91 |
| Date: | 2013–08 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:ifsewp:13/19&r=dcm |
| By: | Edward Anderson (The University of Sydney Business School); Cheng Qian |
| Abstract: | We model a situation in which a single firm evaluates competing suppliers and selects just one. Suppliers submit bids involving both price and quality variables. The buyer makes a choice which from the supplier's perspective appears to contain a stochastic element - for example the buyer may have information, which is not shared with the suppliers, and that gives one supplier an advantage in the final choice. We use a discrete choice model of buyer choice (e.g. multinomial logit). Our main result is that the supplier's choice of the quality variables is not affected by the competitive environment. Thus the suppliers compete only on price. We compare this with a second model in which the buyer's weighting on different quality variables is uncertain at the time bids are made. |
| Keywords: | Supplier choice, Quality variables, Nash equilibrium, Types of uncertainty |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:syb:wpbsba:06/2013&r=dcm |
| By: | Asghar, Zahid; Muhammad, Ahmed |
| Abstract: | This study investigates the determinants of food insecurity for both general and farmer households. It is based on Pakistan Social and Living standard Measurement (PSLM) 2007-08 survey conducted by the Federal Bureau of Statistics, Pakistan. After having descriptive analysis of the important determinants of food insecurity, we have used logit model to find the probability for being household secure or insecure. The model is initially fitted with 16 (for general) and 19 (for farmer households) variables, selected from factors identified by previous researchers that affect food insecurity. Twelve out of 19 variables for farmer households are found to be significant such as household size, household size square, household income, number of rooms, dependency ratio, electricity connection, irrigation facility, age and age square of household head. To our surprise female education variable is insignificant for general household model. The results obtained are further analyzed to compute partial effects on continuous variables and change in the probabilities on discrete variables for the significant factors in the logistic models. Household size, education of household head, annual income and agricultural income are some of the most important factors influencing the household’s food insecurity status. |
| Keywords: | Food Security, Discrete Choice Model |
| JEL: | C1 C5 Q18 |
| Date: | 2013–08–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:21510&r=dcm |
| By: | Andrey L. Vasnev (The University of Sydney Business School); Laurent L. Pauwels |
| Abstract: | The problem of finding appropriate weights to combine several density forecasts is an important issue currently debated in the forecast combination literature. Recently, a paper by Hall and Mitchell (IJF, 2007) proposes to combine density forecasts with optimal weights obtained from solving an optimization problem. This paper studies the properties of this optimization problem when the number of forecasting periods is relatively small and finds that it often produces corner solutions by allocating all the weight to one density forecast only. This paper's practical recommendation is to have an additional training sample period for the optimal weights. While reserving a portion of the data for parameter estimation and making pseudo-out-of-sample forecasts are common practices in the empirical literature, employing a separate training sample for the optimal weights is novel, and it is suggested because it decreases the chances of corner solutions. Alternative log-score or quadratic-score weighting schemes do not have this training sample requirement. |
| Keywords: | Forecast combination; Density forecast; Optimization; Optimal weight; Discrete choice models |
| Date: | 2013–01 |
| URL: | http://d.repec.org/n?u=RePEc:syb:wpbsba:01/2013&r=dcm |
| By: | Liping Gao; Hyeongwoo Kim; Yaoqi Zhang |
| Abstract: | This paper empirically investigates potential effects of economic recessions on consumers¡¯ decision making process for recreational activities using the Consumer Expenditure Survey (CES) data during the Great Recession. We employ the Probit model to study how changes in income affect the likelihood of making non-zero expenditures on entertainment activities. We also use the Tobit model to assess the income effect on those activities in the presence of censored observations. We found overall statistically significant effects of recessions on leisure activities, which may explain sluggish adjustments of leisure consumption during recessions. |
| Keywords: | Entertainment; Consumer Expenditure Survey; Probit Model; Tobit Model |
| JEL: | D12 J01 P46 |
| Date: | 2013–08 |
| URL: | http://d.repec.org/n?u=RePEc:abn:wpaper:auwp2013-09&r=dcm |