LDV Models Research Articles

Lane-based Distance-Velocity model for evaluating pedestrian-vehicle interaction at non-signalized locations

Pedestrian vehicle conflicts at non-signalized crosswalks are a world-wide safety concern. Although the “pedestrian priority” policy is applied in some regions to improve pedestrian safety, its effect needs further investigation. This study proposes the Lane-based Distance-Velocity model (LDV) to investigate pedestrian-vehicle interaction at non-signalized crosswalks. Compared with the DV model, the LDV model considers the lateral distance between vehicles and pedestrians. Therefore, the LDV model extends the application of the DV model by allowing it to be applied not only on one-lane streets to multi-lane streets. The conflict severities of pedestrian-vehicle interaction in the LDV model are classified into four categories: safe-passage, mild-interaction, potential-conflict and potential-collision. Based on that, pedestrian crossing decisions are graded as safe-crossing, risky-crossing, and dangerous-crossing. The experimental data are collected at a non-signalized crosswalk through drone footage collected in Xi’an City (China) with a Machine Vision Intelligent Algorithm. The model is tested through a case study to evaluate pedestrian crossing safety when interacting with private cars and taxis. Results from the case study suggest that the proposed model works well in the pedestrian-vehicle interaction analysis. Firstly, 87.9% of drivers are willing to provide right-of-way to pedestrians when they have enough time to react and yield. Then, both the DV model and LDV model have reached consistent conclusions: the deliberate violation rate (DVR) of taxi drivers is 22.64%, which is double that of private car drivers. Last, taxis commit a higher percentage of pedestrians' dangerous or risky crossing situations than private cars. Relevant government departments can utilize the results of this study to manage urban traffic better and improve pedestrian safety.

Beyond Performance: Racial Prejudice and Whites' Mistrust of Government.

Scholars have argued that racial policy beliefs contributed to a decline in public trust among white-Americans, but this effect waned over time as racial policies left the agenda. We theorize that beliefs about racial policies may have been integrated into whites’ racial attitudes, resulting in a durable association between racial prejudice and public trust. Our analysis of eight ANES surveys (1992–2020) shows that racial prejudice, measured in terms of anti-Black stereotypes, informs white Americans’ beliefs about the trustworthiness of the federal government. LDV models strengthen our contention by showing that the relationship persists after an LDV is included and it is not reciprocal.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11109-022-09774-6.

Impact of secondhand smoke exposure on cognitive function among middle-aged and older women in China: findings from three waves of the China Health and Retirement Longitudinal Study

ObjectivesTo examine the association between secondhand smoke (SSH) and women’s global cognitive function and cognitive subdomains.DesignCohort study.ParticipantsData for this study were obtained from the China Health and Retirement Longitudinal Study...

Echoes of the 'White Republic': Racial Prejudice, Xenophobia and the Erosion of Democracy in the United States

We argue that in a racially and ethnically diverse society such as the U.S., public support for anti-democratic norms among the white majority may be driven, in part by threat related to immigrants. Following racial priming theory, we suggest that for members of the white majority who harbor strong negative priors about immigrants, immigrant-origin groups’ demands for democratic inclusion may be perceived in zero-sum terms. We further argue that threat to the white cultural primacy by outgroups may drive anti-immigrant whites to support anti-democratic norms that may better protect the elevated social status of whites over democratic norms that extend equality and cultural representation to racialized immigrant groups. We test this theory via two original threat priming experiments and an LDV analysis using 2017-2018 panel data from the VSG. Our findings suggest that when threat from immigrants is salient, it causes declining support for democratic norms among anti-immigrant whites. The LDV models also show that anti-immigrant attitudes are a strong and positive predictor of support for anti-democratic norms even accounting for the lagged DV.

Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles

The purpose of this study is to investigate possible improvements in ICEVs by implementing fuzzy logic-based parallel hard-type power hybrid systems. Two types of conventional ICEVs (gasoline and diesel) and two types of HEVs (gasoline-electric, diesel electric) were generated using vehicle and powertrain simulation tools and a Matlab-Simulink application programming interface. For gasoline and gasoline-electric HEV vehicles, the prediction accuracy for four types of LDV models was validated by conducting comparative analysis with the chassis dynamometer and OBD test data. The predicted results show strong correlation with the test data. The operating points of internal combustion engines and electric motors are well controlled in the high efficiency region and battery SOC was well controlled within ±1.6%. However, for diesel vehicles, we generated virtual diesel-electric HEV vehicle because there is no available vehicles with similar engine and vehicle specifications with ICE vehicle. Using a fuzzy logic-based parallel hybrid system in conventional ICEVs demonstrated that HEVs showed superior performance in terms of fuel consumption and CO2 emission in most driving modes.

Financing Constraints and a Firm's Decision and Ability to Innovate: Establishing Direct and Reverse Effects

The paper analyzes the existence and impact of …nancing constraints as a possibly serious obstacle to innovation by …rms. Direct measures of …nancing constraints are employed using survey data collected by the Banque de France and Eurostat, which overcomes the problems with the traditional approach of trying to deduce indirectly the existence and impact of …nancing constraints through the signi…cance of …rm wealth variables. The importance of using direct as opposed to indirect measures of …nancing constraints has been illustrated recently by two articles in this Journal (Moyen (2004) using a synthetic sample methodology, and Hennessy and Whited (2007) through the method of simulated moments). The econometric framework we employ in our study is the simultaneous bivariate probit with mutual endogeneity of direct indicators of …nancial constraints and innovation decisions by …rms. The pa- per discusses the important identi…cation issue of coherency conditions in such LDV models with endogeneity and ‡exible temporal and contemporaneous correlations in the unobservable error terms. Our novel methods for establishing coherency condi- tions allow us for the …rst time to estimate models hitherto classi…ed as incoherent through the use of prior sign restrictions on model parameters. We are thus able to quantify the interaction between …nancing constraints and a …rm’s decision and ability to innovate without forcing the econometric models to be recursive. Hence, we obtain direct as well as reverse interaction e¤ects, leading us to conclude that binding …nancing constraints discourage innovation and at the same time innovative …rms are more likely to face binding …nancing constraints.

Inverse Regression in Binary Response LDV Model

Sliced inverse regression, a link-free and distribution-free method, is applied to binary response limited dependent variable models. An inverse regression property of binary response LDV model is found. Based on this property, if the distributions of X j (j = 1, 2,…, p) satisfy the linearity condition, then β can be estimated up to a positive multiplicative scalar without any assumptions on the distribution of error ϵ. Moreover, the estimator can be proved to be asymptotically normal based on which testing hypotheses are considered. Simulations results are reported.

Pseudospectral versus finite-difference schemes in the numerical integration of stochastic models of surface growth

We present a comparison between finite differences schemes and a pseudospectral method applied to the numerical integration of stochastic partial differential equations that model surface growth. We have studied, in 1+1 dimensions, the Kardar, Parisi, and Zhang model (KPZ) and the Lai, Das Sarma, and Villain model (LDV). The pseudospectral method appears to be the most stable for a given time step for both models. This means that the time up to which we can follow the temporal evolution of a given system is larger for the pseudospectral method. Moreover, for the KPZ model, a pseudospectral scheme gives results closer to the predictions of the continuum model than those obtained through finite difference methods. On the other hand, some numerical instabilities appearing with finite difference methods for the LDV model are absent when a pseudospectral integration is performed. These numerical instabilities give rise to an approximate multiscaling observed in earlier numerical simulations. With the pseudospectral approach no multiscaling is seen in agreement with the continuum model.

Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors*

AbstractThe paper investigates the causes of currency crises in emerging markets. We estimate the probability of a currency crisis by applying maximum smoothly simulated likelihood to a dynamic LDV model. This approach allows us to take explicit account of the existence of intertemporal links between crises. The results show that currency crises are influenced by real, monetary, debt and global variables. Past banking crises are significant determinants of the probability of currency crises. Moreover, countries that sharply devalued in the past are less prone to experience another currency crisis. We find evidence of unobserved heterogeneity, which may reflect differences in the countries’ institutional/historical background. Finally, the determinants of currency crises differ by type of exchange rate regime.

Suspended sand transport in different conditions of temperature and salinity

A study on the action of temperature and salinity on the distribution of suspended sand concentration and transport rate has been carried out through a lDV model with a proposed formula of the kinematic viscosity. Five tests of the data sets from the Delta flume with three different cases of temperature and salinity were used for the simulation. The results of computation showed that the vertical distributions of suspended sand concentration depend on salinity and specially, on temperature. When temperature increases or salinity decreases, the settling process of particles occurs faster. For fine sand, the discrepancy on transport rates due to temperature or salinity decreases with wave height. For coarse sand, the effect of temperature and salinity is not much affected by the wave height. The lDV model showed good ability to simulate the time-averaged suspended sand concentrations and hence the suspended transport in the ripple regime, provided that the reference concentration near the bed and the vortex-related mixing are represented with sufficient accuracy. Therefore; it can be used effectively to study the behaviour of some physical parameters on the transport.

Estimation of quantity games in the presence of indivisibilities and heterogeneous firms

Abstract This paper presents a theoretical framework that allows estimation of game theoretic models of quantity competition, including a non-trivial class of differentiated product quantity games. The simplest examples of quantity games are entry games, where the strategy each firm i makes is discrete, s i ∈ S i = { 0 , 1 } (do not enter/enter). I consider a general class of games where strategy sets are “chains”, which includes the situation where they are a finite set of integers, S i = { 0 , 1 , … , M } . In addition, I assume that profits of each firm can be written as a function of the firm's own strategy s i and a possibly parametric index of market output, Q ( s i , s - i ; θ 1 ) , so that π i ( s i , s - i ; θ ) = Ψ i ( s i , Q ( s i , s - i ; θ 1 ) ; θ 2 ) where θ = ( θ 1 , θ 2 ) . The main theoretical result in the paper establishes easily verifiable conditions under which the index of market output Q ( s i , s - i ; θ 1 ) is uniquely determined within the set of Nash equilibria of the game. The model's parameters may then be estimated by comparing the predicted index of market output in a cross section of markets. The paper provides both a generalization and an extension of the theoretical results developed by Bresnahan and Reiss (1991. Empirical models of discrete games. Journal of Econometrics 48, 57–82.) and Berry (1992. Estimation of a model of entry in the airline industry. Econometrica 60 (4), 887–917.), which allowed estimation of the homogeneous products entry game and where the index of market output was the number of active firms, Q ( s i , s - i ) = ∑ i = 1 N s i , with s i ∈ { 0 , 1 } . I illustrate one member of the class of models that these results allow us to estimate by developing a model of discrete quantity competition using count data from the supermarket industry. The discrete quantity game is the game theoretic analogue to ordered LDV models such as the ordered probit model.

IDV model for suspended sand transport under waves in ripple regime

In this paper the results of theoretical studies on suspended sand transport under irregular waves in the ripple regime are presented. The results from the lDV model, which simulates the instantaneous velocity and sand concentration from close to the bed up to higher in the water column are obtained. The model is based on the classical diffusion approach taking both the turbulence-related and the effective wave related diffusion into account. It shows that the time-averaged sand concentrations can be simulated reasonably well in the ripple regime using calibrated equations. Especially, the proposed formula for the diffusion coefficient by wave, considerably improved the behavior of vertical distribution of upended sediment concentration. Finally, the wave related suspended sediment transport in depth-integration is computed and compared with the measured data. The accuracy of the suspended transport was found to be strongly dependent on using measured data or predictive formula for concentration at the bed boundary.

The Method of Simulated Scores for the Estimation of LDV Models

The method of simulated scores (MSS) is presented for estimating limited dependent variables models (LDV) with flexible correlation structure in the unobservables. We propose simulators that are continuous in the unknown parameter vectors, and hence standard optimization methods can be used to compute the MSS estimators that employ these simulators. The first continuous method relies on a recursive conditioning of the multivariate normal density through a Cholesky triangularization of its variance-covariance matrix. The second method combines results about the conditionals of the multivariate normal distribution with Gibbs resampling techniques. We establish consistency and asymptotic normality of the MSS estimators and derive suitable rates at which the number of simulations must rise if biased simulators are used.