nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2017‒09‒17
three papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Reliable estimation of random coefficient logit demand models By Brunner, Daniel; Heiss, Florian; Romahn, André; Weiser, Constantin
  2. What drives gross flows in equity and investment fund shares in Luxembourg? By Gabriele di Filippo
  3. Bottleneck models and departure time problems By André De Palma; Claude Lefèvre

  1. By: Brunner, Daniel; Heiss, Florian; Romahn, André; Weiser, Constantin
    Abstract: The differentiated demand model of Berry, Levinsohn and Pakes (1995) is widely used in empirical economic research. Previous literature has demonstrated numerical instabilities of the corresponding GMM estimator that give a wide range of parameter estimates and economic implications depending on technical details such as the choice of optimization algorithm, starting values, and convergence criteria. We show that these instabilities are mainly driven by numerical approximation errors of the moment function which is not analytically available. With accurate approximation, the estimator is well-behaved. We also discuss approaches to mitigate the computational burden of accurate approximation and provide code for download.
    Date: 2017
  2. By: Gabriele di Filippo
    Abstract: The paper analyses gross portfolio investment flows in equity and investment fund shares (EIFS) in Luxembourg - a small open economy with a financial center - over the period 2002Q1- 2016Q3. The statistical analysis shows that gross EIFS flows exhibit similar patterns over time amongst resident investors and non-resident investors. However, the volatility of EIFS flows instigated by non-resident investors is larger than the volatility of EIFS flows initiated by resident investors. The graphical analysis provides evidence that gross EIFS flows switch between positive and negative growth cycles whose durations vary over time, depending on macroeconomic, financial and geopolitical shocks at the global level. In particular, gross EIFS flows correlate positively with stock returns and negatively with risk/uncertainty measures at the global level. Sudden and sharp increases (decreases) in gross EIFS flows concur with periods of bullish (bearish) equity markets and low (heightened) risk aversion. Econometric tests show that gross EIFS flows (including extreme movements) are driven by macroeconomic and financial variables at the global level. Eventually, a prediction exercise suggests that it is difficult to forecast extreme movements in gross EIFS flows based on global macroeconomic and financial variables.
    Keywords: International finance, external statistics, balance of payments, equity and investment fund shares, gross flows, surges/flights, stops/retrenchments, graphical analysis, GMM estimation, discrete choice model, ROC analysis, prediction exercise
    JEL: C51 F3 F37 G15
    Date: 2017–08
  3. By: André De Palma (ENS Cachan - École normale supérieure - Cachan, Université Paris-Saclay); Claude Lefèvre (ULB - Université Libre de Bruxelles [Bruxelles])
    Abstract: This paper is concerned with the problem of departure times in dynamic bottleneck models. First, the case of a set of individual drivers is discussed through both deterministic and stochastic approaches. Then, the analysis is extended to a new model that combines small and large agents. In the stochastic setting, our focus is mainly on the model building and simulations will be carried out in a near future.
    Keywords: dynamic bottleneck models,congestion,equilibrium,deterministic version,stochastic approach,small and large agents,discrete choice models
    Date: 2017–09–04

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