nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2012‒03‒28
six papers chosen by
Philip Yu
Hong Kong University

  1. The training and job decisions of nurses: the first year of a longitudinal study investigating nurse recruitment and retention. CHERE Working Paper 2012/02 By Patricia Kenny; Denise Doiron; Jane Hall; Deborah J Street; Kathleen Milton-Wildey; Glenda Parmenter
  2. An Epistemic Rationale for Order-Independence By Michael Trost
  3. Is china climbing up the quality ladder? By Gabor Pula; Daniel Santabárbara
  4. Forecasting adoption of ultra-low-emission vehicles using the GHK simulator and Bayes estimates of a multinomial probit model By Daziano, Ricardo A.; Achtnicht, Martin
  5. EDUCATION AND LABOUR MARKET OUTCOMES: EVIDENCE FROM INDIA By Geraint Johnes; A Aggarwal; R Freguglia; G Spricigo
  6. Model Adequacy Checks for Discrete Choice Dynamic Models By Igor Kheifets; Carlos Velasco

  1. By: Patricia Kenny (CHERE, University of Technology, Sydney); Denise Doiron; Jane Hall (CHERE, University of Technology, Sydney); Deborah J Street (University of Technology, Sydney); Kathleen Milton-Wildey; Glenda Parmenter
    Abstract: Understanding the employment choices and preferences of new entrants to the nursing profession is an important element in the formulation of policies for ensuring an adequate supply of nurses to meet population healthcare needs in the coming decades. A longitudinal cohort study to investigate the job preferences of nursing students and new graduates commenced in New South Wales in 2008. The study aimed to identify the relative importance of job attributes as well as factors such as age, family structure, education and health in nursesÂ’ employment choices. In addition to studying actual choices, it uses repeated discrete choice experiments (DCE) to measure preferences for job attributes and how these change after graduation and throughout the early career years. Data collection by annual online surveys commenced in September 2009 and, after one year, 530 participants had completed the first survey. This paper describes the characteristics of this cohort; it also provides an outline of the study and its methods.
    Keywords: Discrete choice experiments, nursing workforce, employment
    JEL: I1 I19 J2 J24
    Date: 2012–02
  2. By: Michael Trost (Albert Ludwig University Freiburg, and Max Planck Institute of Economics, Jena)
    Abstract: The issue of the order-dependence of iterative deletion processes is well-known in the game theory community, and meanwhile conditions on the dominance concept underlying these processes have been detected which ensure order-independence (see e.g. the criteria of Gilboa et al., 1990 and Apt, 2011). While this kind of research deals with the technical issue, whether certain iterative deletion processes are order-independent, or not, our focus is on the normative issue, whether there are good reasons for employing order-independent iterative deletion processes on strategic games. We tackle this question from an epistemic perspective and attempt to figure out, whether order-independence contains some specific epistemic meaning. It turns out that, under fairly general preconditions on the choice rules underlying the iterative deletion processes, the order-independence of these deletion processes coincides with the epistemic characterization of their solutions by the common belief of choice-rule following behavior. The presumably most challenging precondition of this coincidence is the property of the independence of irrelevant acts. We also examine the consequences of two weakenings of this property on our epistemic motivation for order-independence. Although the coincidence mentioned above breaks down for both weakenings, still there exist interesting links between the order-independence of iterative deletion processes and the common belief of following the choice rules, on which these processes are based.
    Keywords: Iterative deletion process, order-independence, choice rule, epistemic game theory
    JEL: C72 D83
    Date: 2012–03–20
  3. By: Gabor Pula (European Central Bank); Daniel Santabárbara (Banco de España)
    Abstract: There is an ongoing debate in the literature about the quality content of Chinese exports and to what extent China poses a threat to the market positions of advanced economies. While China’s export structure is very similar to that of the advanced world, its export unit values are well below the level of developed economies. Building on the assumption that unit values reflect quality, the prevailing view of the literature is that China exports low quality varieties of the same products as its advanced competitors. This paper challenges this view by relaxing the assumption that unit values reflect quality. We derive the quality of Chinese exports to the European Union by estimating disaggregated demand functions from a discrete choice model. The paper has three major findings. First, China’s share of the European Union market is larger than would be justified only by its low average prices, implying that the quality of Chinese exports is high compared to many competitors. Second, China has gained quality relative to other competitors since 1995, indicating that China is climbing up the quality ladder. Finally, our analysis of the supply side determinants reveals that the relatively high quality of Chinese exports is related to processing trade and the increasing role of global production networks in China.
    Keywords: Chinese exports, vertical product differentiation, quality ladder, global production networks, discrete choice model, COMEXT database
    JEL: F1 F12 F14 F15 F23
    Date: 2012–02
  4. By: Daziano, Ricardo A.; Achtnicht, Martin
    Abstract: In this paper we use Bayes estimates of a multinomial probit model with fully flexible substitution patterns to forecast consumer response to ultra-low-emission vehicles. In this empirical application of the probit Gibbs sampler, we use stated-preference data on vehicle choice from a Germany-wide survey of potential light-duty-vehicle buyers using computer-assisted personal interviewing. We show that Bayesian estimation of a multinomial probit model with a full covariance matrix is feasible for this medium-scale problem. Using the posterior distribution of the parameters of the vehicle choice model as well as the GHK simulator we derive the choice probabilities of the different alternatives. We first show that the Bayes point estimates of the market shares reproduce the observed values. Then, we define a base scenario of vehicle attributes that aims at representing an average of the current vehicle choice situation in Germany. Consumer response to qualitative changes in the base scenario is subsequently studied. In particular, we analyze the effect of increasing the network of service stations for charging electric vehicles as well as for refueling hydrogen. The result is the posterior distribution of the choice probabilities that represent adoption of the energy-effcient technologies. --
    Keywords: Discrete choice models,Bayesian econometrics,Low emission vehicles,Charging infrastructure
    JEL: C25 D12 Q42
    Date: 2012
  5. By: Geraint Johnes; A Aggarwal; R Freguglia; G Spricigo
    Abstract: The impact of education on labour market outcomes is analysed using data from various rounds of the National Sample Survey of India. Occupational destination is examined using both multinomial logit analyses and structural dynamic discrete choice modelling. The latter approach involves the use of a novel approach to constructing a pseudo-panel from repeated cross-section data, and is particularly useful as a means of evaluating policy impacts over time. We find that policy to expand educational provision leads initially to an increased takeup of education, and in the longer term leads to an increased propensity for workers to enter non-manual employment.
    Date: 2011
  6. By: Igor Kheifets (New Economic School, Moscow); Carlos Velasco (Department of Economics, Universidad Carlos III de Madrid)
    Abstract: This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct specification of parametric conditional distributions in dynamic discrete choice models, not only of some particular conditional characteristics such as moments or symmetry. Knowing the true distribution is important in many circumstances, in particular to apply efficient maximum likelihood methods, obtain consistent estimates of partial effects and appropriate predictions of the probability of future events. We propose a transformation of data which under the true conditional distribution leads to continuous uniform iid series. The uniformity and serial independence of the new series is then examined simultaneously. The transformation can be considered as an extension of the integral transform tool for noncontinuous data. We derive asymptotic properties of such tests taking into account the parameter estimation effect. Since transformed series are iid we do not require any mixing conditions and asymptotic results illustrate the double simultaneous checking nature of our test. The test statistics converges under the null with a parametric rate to the asymptotic distribution, which is case dependent, hence we justify a parametric bootstrap approximation. The test has power against local alternatives and is consistent. The performance of the new tests is compared with classical specification checks for discrete choice models.
    Keywords: Goodness of fit, diagnostic test, parametric conditional distribution, discrete choice models, parameter estimation effect, bootstrap
    JEL: C12 C22 C52
    Date: 2012–02

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