Handling initial conditions/state dependence in binary data

2011 ◽  
pp. 193-218
Keyword(s):  
Binary Data ◽  
Initial Conditions ◽  
State Dependence

Habit Formation in Tourism Traveling

2020 ◽  
pp. 004728752096459
Author(s):  
David Boto-García
Keyword(s):  
Habit Formation ◽  
Initial Conditions ◽  
State Dependence ◽  
Climate Conditions ◽  
Unemployment Rates ◽  
Probit Models ◽  
Percentage Points ◽  
Price Indexes ◽  
Individual Participation

This article conducts a microeconometric analysis of individual participation in tourism activities. We examine the existence of habit formation in the form of state dependence by which past trips increase the taste for traveling. We also study the role of regional unemployment rates, regional price indexes, and climate conditions at origin on the likelihood of tourism participation. Individual and household characteristics are also controlled for. We use monthly longitudinal microdata for Spain between 2015 and 2018 involving more than 92,000 individuals. We estimate static and dynamic random effects Probit models finding evidence of habit formation. The initial conditions and participation in the previous month raise the propensity to make a tourist trip in the following period by 28 percentage points. Habit formation is found to be strongly associated with income and education.

scholarly journals Assessing poverty persistence in households with children

2020 ◽  
Vol 18 (4) ◽  
pp. 551-569
Author(s):  
Enrico Fabrizi ◽  
Chiara Mussida
Keyword(s):  
Initial Conditions ◽  
State Dependence ◽  
Single Measure ◽  
Poverty Measure ◽  
Household Level ◽  
Household Characteristics ◽  
Strong State ◽  
Poverty Persistence ◽  
Alternative Measures ◽  
Households With Children

Abstract The analysis of poverty persistence received considerable attention in recent years. In this paper we explore the role of the adopted poverty measure in the analysis of its persistence. Specifically, we consider three measures: the risk of poverty, the severe material deprivation and subjective poverty, motivated by the understanding of poverty as a complex phenomenon and for which no single measure can effectively capture its several dimensions. The empirical analysis is based on the 2013-2016 longitudinal sample of the EU-SILC survey. We focus on Italian households with dependent children. We apply a correlated random effects probit models with endogenous initial conditions to assess genuine state dependence after controlling for structural household characteristics and variables related to participation in the labour market. A strong state dependence emerges, regardless of the considered poverty measure thus providing evidence of poverty and social exclusion persistence. We also find evidence of relevance of initial conditions for all measures in focus. Nonetheless, structural household characteristics and household level economic variables play roles that are often different in the three parallel models; these differences are consistent with the aims and nature of the alternative measures.

Toward an Uncertainty Budget for a Coastal Ocean Model

2011 ◽  
Vol 139 (3) ◽  
pp. 866-884 ◽  
Author(s):  
Sangil Kim ◽  
R. M. Samelson ◽  
Chris Snyder
Keyword(s):  
Boundary Condition ◽  
Root Mean Square ◽  
Initial Conditions ◽  
State Dependence ◽  
Uncertainty Budget ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Wind Forcing ◽  
Mean Square ◽  
Coastal Ocean Model

Abstract Estimates of three components of an uncertainty budget for a coastal ocean model in a wind-forced regime are made based on numerical simulations. The budget components behave differently in the shelf regime, inshore of the 200-m isobath, and the slope-interior regime, between the 200-m isobath and a fixed longitude (126°W) that is roughly 150 km offshore. The first of the three budget components is an estimate of the uncertainty in the ocean state given only a known history of wind stress forcing, with errors in the wind forcing estimated from differences between operational analyses. It is found that, over the continental shelf, the response to wind forcing is sufficiently strong and deterministic that significant skill in estimating shelf circulation can be achieved with knowledge only of the wind forcing, and no ocean data, for wind fields with these estimated errors. The second involves initial condition error and its influence on uncertainty, including both error growth with time from well-known initial conditions and error decay with time from poorly known initial conditions but with well-known wind forcing. The third component is that of boundary condition error and its influence on the interior solutions, including the dependence of that influence on the specific location along the boundary of the boundary condition error. Boundary condition errors with amplitude comparable to the root-mean-square variability at the boundary lead eventually to errors equal to the root-mean-square variability in the slope-interior regime, and somewhat smaller errors in the shelf regime. Covariance estimates based on differences of the wind-forced solutions from the ensemble mean are not dramatically different from those based on the full fields, and do not show strong state dependence.

State-Dependent Demand Estimation with Initial Conditions Correction

2020 ◽  
Vol 57 (5) ◽  
pp. 789-809
Author(s):  
Andrey Simonov ◽  
Jean-Pierre Dubé ◽  
Günter Hitsch ◽  
Peter Rossi
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Initial Conditions ◽  
Brand Choice ◽  
State Dependence ◽  
The State ◽  
Data Sets ◽  
True Parameter ◽  
State Dependent ◽  
Initial Conditions Problem

The authors analyze the initial conditions bias in the estimation of brand choice models with structural state dependence. Using a combination of Monte Carlo simulations and empirical case studies of shopping panels, they show that popular, simple solutions that misspecify the initial conditions are likely to lead to bias even in relatively long panel data sets. The magnitude of the bias in the state dependence parameter can be as large as a factor of 2–2.5. The authors propose a solution to the initial conditions problem that samples the initial states as auxiliary variables in a Markov chain Monte Carlo procedure. The approach assumes that the joint distribution of prices and consumer choices is in equilibrium, which is plausible for the mature consumer packaged goods products commonly used in empirical applications. In Monte Carlo simulations, the approach recovers the true parameter values even in relatively short panels. Finally, the authors propose a diagnostic tool that uses common, biased approaches to bound the values of the state dependence and construct a computationally light test for state dependence.

scholarly journals Analysis of the Conformally Flat Approximation for Binary Neutron Star Initial Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
In-Saeng Suh ◽  
Grant J. Mathews ◽  
J. Reese Haywood ◽  
N. Q. Lan
Keyword(s):  
Neutron Stars ◽  
Initial Conditions ◽  
State Dependence ◽  
Einstein Equations ◽  
Conformally Flat ◽  
Binary Neutron Star ◽  
Stable Circular Orbit ◽  
Flat Condition ◽  
Binary Neutron Stars ◽  
The Stability

The spatially conformally flat approximation (CFA) is a viable method to deduce initial conditions for the subsequent evolution of binary neutron stars employing the full Einstein equations. Here we analyze the viability of the CFA for the general relativistic hydrodynamic initial conditions of binary neutron stars. We illustrate the stability of the conformally flat condition on the hydrodynamics by numerically evolving ~100 quasicircular orbits. We illustrate the use of this approximation for orbiting neutron stars in the quasicircular orbit approximation to demonstrate the equation of state dependence of these initial conditions and how they might affect the emergent gravitational wave frequency as the stars approach the innermost stable circular orbit.

The Beck Hopelessness Scale

2016 ◽  
Vol 32 (2) ◽  
pp. 111-118 ◽  
Author(s):  
Marianna Szabó ◽  
Veronika Mészáros ◽  
Judit Sallay ◽  
Gyöngyi Ajtay ◽  
Viktor Boross ◽  
...  
Keyword(s):  
Binary Data ◽  
Factor Model ◽  
Clinical Sample ◽  
Analytical Techniques ◽  
Cross Cultural ◽  
Cultural Validity ◽  
Beck Hopelessness Scale ◽  
Method Effects ◽  
Hungarian Population ◽  
Components Analysis

Abstract. The aim of the present study was to examine the construct and cross-cultural validity of the Beck Hopelessness Scale (BHS; Beck, Weissman, Lester, & Trexler, 1974 ). Beck et al. applied exploratory Principal Components Analysis and argued that the scale measured three specific components (affective, motivational, and cognitive). Subsequent studies identified one, two, three, or more factors, highlighting a lack of clarity regarding the scale’s construct validity. In a large clinical sample, we tested the original three-factor model and explored alternative models using both confirmatory and exploratory factor analytical techniques appropriate for analyzing binary data. In doing so, we investigated whether method variance needs to be taken into account in understanding the structure of the BHS. Our findings supported a bifactor model that explicitly included method effects. We concluded that the BHS measures a single underlying construct of hopelessness, and that an incorporation of method effects consolidates previous findings where positively and negatively worded items loaded on separate factors. Our study further contributes to establishing the cross-cultural validity of this instrument by showing that BHS scores differentiate between depressed, anxious, and nonclinical groups in a Hungarian population.

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