共查询到20条相似文献,搜索用时 10 毫秒
1.
Santiago Acerenza Otávio Bartalotti Désiré Kédagni 《Journal of Applied Econometrics》2023,38(3):407-422
This paper considers the bivariate probit model's identifying assumptions: linear index specification, joint normality of errors, instrument exogeneity, and relevance. First, we develop sharp testable equalities that detect all possible observable violations of the assumptions. Second, we propose an easy-to-implement testing procedure for the model's validity using existing inference methods for intersection bounds. The test achieves correct empirical size and performs well in detecting violations of the conditions in simulations. Finally, we provide a road map on what to do when the bivariate probit model is rejected, including novel bounds for the average treatment effect that relax the normality assumption. 相似文献
2.
The purpose of this paper is to provide guidelines for empirical researchers who use a class of bivariate threshold crossing models with dummy endogenous variables. A common practice employed by the researchers is the specification of the joint distribution of unobservables as a bivariate normal distribution, which results in a bivariate probit model. To address the problem of misspecification in this practice, we propose an easy‐to‐implement semiparametric estimation framework with parametric copula and nonparametric marginal distributions. We establish asymptotic theory, including root‐n normality, for the sieve maximum likelihood estimators that can be used to conduct inference on the individual structural parameters and the average treatment effect (ATE). In order to show the practical relevance of the proposed framework, we conduct a sensitivity analysis via extensive Monte Carlo simulation exercises. The results suggest that estimates of the parameters, especially the ATE, are sensitive to parametric specification, while semiparametric estimation exhibits robustness to underlying data‐generating processes. We then provide an empirical illustration where we estimate the effect of health insurance on doctor visits. In this paper, we also show that the absence of excluded instruments may result in identification failure, in contrast to what some practitioners believe. 相似文献
3.
This paper analyzes spatial Probit models for cross sectional dependent data in a binary choice context. Observations are divided by pairwise groups and bivariate normal distributions are specified within each group. Partial maximum likelihood estimators are introduced and they are shown to be consistent and asymptotically normal under some regularity conditions. Consistent covariance matrix estimators are also provided. Estimates of average partial effects can also be obtained once we characterize the conditional distribution of the latent error. Finally, a simulation study shows the advantages of our new estimation procedure in this setting. Our proposed partial maximum likelihood estimators are shown to be more efficient than the generalized method of moments counterparts. 相似文献
4.
In this paper we consider semiparametric estimation of a generalized correlation coefficient in a generalized bivariate probit model. The generalized correlation coefficient provides a simple summary statistic measuring the relationship between the two binary decision processes in a general framework. Our semiparametric estimation procedure consists of two steps, combining semiparametric estimators for univariate binary choice models with the method of maximum likelihood for the bivariate probit model with nonparametrically generated regressors. The estimator is shown to be consistent and asymptotically normal. The estimator performs well in our simulation study. 相似文献
5.
We propose several Lagrange multiplier tests of logit and probit models, which may be inexpen- sively computed by means of artificial linear regressions. These maybe used to test for various forms of model inadequacy, including the omission of specified variables and heteroskedasticity of known form. We perform a number of sampling experiments, in which we compare the small-sam- ple properties of these tests and of likelihood ratio tests. One of the LM tests turns out to have better small-sample properties than any of the others. We then investigate the power of the tests against local alternatives, and conduct a further series of sampling experiments to compare the power of various tests. 相似文献
6.
António Antunes Diana Bonfim Nuno Monteiro Paulo M.M. Rodrigues 《International Journal of Forecasting》2018,34(2):249-275
Banking crises are rare events, but when they occur, their consequences are often dramatic. The aim of this paper is to contribute to the toolkit of early warning models that is available to policy makers by exploring the dynamics and exuberances embedded in a panel dataset that covers 22 European countries over four decades (from 1970Q1 to 2012Q4). The in- and out-of-sample forecast performances of several (dynamic) probit models are evaluated, with the objective of developing common vulnerability indicators with early warning properties. The results obtained show that adding dynamic components and exuberance indicators to the models improves the performances of early warning models significantly. 相似文献
7.
Maximum Likelihood (ML) estimation of probit models with correlated errors typically requires high-dimensional truncated integration. Prominent examples of such models are multinomial probit models and binomial panel probit models with serially correlated errors. In this paper we propose to use a generic procedure known as Efficient Importance Sampling (EIS) for the evaluation of likelihood functions for probit models with correlated errors. Our proposed EIS algorithm covers the standard GHK probability simulator as a special case. We perform a set of Monte Carlo experiments in order to illustrate the relative performance of both procedures for the estimation of a multinomial multiperiod probit model. Our results indicate substantial numerical efficiency gains for ML estimates based on the GHK–EIS procedure relative to those obtained by using the GHK procedure. 相似文献
8.
Many applied researchers of limited dependent variable models found it disadvantageous that a widely accepted Pseudo-R2 does not exist for this type of estimation. The paper provides guidance for researchers in choosing a Pseudo-R2 in the binary probit case. The starting point is that R2 is best understood in the ordinary least squares (OLS) case with continuous data, which is chosen as the reference situation. It is considered which Pseudo-R2 is best able to mimic the OLS-R2. The results are surprisingly clear: a measure suggested by McKelvey-Zavoina performs the best under our criterion. However, in the more likely case of low Pseudo-R2's, a normalization of a measure proposed by Aldrich-Nelson which we suggest is almost as good as the McKelvey-Zavoina, and is in general easier to calculate. We also show that if the underlying R2 is predicted using cubic regressions given the Pseudo-R2, all measures perform much better. 相似文献
9.
Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper, I characterize the leading term of a large-T expansion of the bias of the MLE and estimators of average marginal effects in parametric fixed effects panel binary choice models. For probit index coefficients, the former term is proportional to the true value of the coefficients being estimated. This result allows me to derive a lower bound for the bias of the MLE. I then show that the resulting fixed effects estimates of ratios of coefficients and average marginal effects exhibit no bias in the absence of heterogeneity and negligible bias for a wide variety of distributions of regressors and individual effects in the presence of heterogeneity. I subsequently propose new bias-corrected estimators of index coefficients and marginal effects with improved finite sample properties for linear and nonlinear models with predetermined regressors. 相似文献
10.
A random variableY is right tail increasing (RTI) inX if the failure rate of the conditional distribution ofX givenY>y is uniformly smaller than that of the marginal distribution ofX for everyy0. This concept of positive dependence is not symmetric inX andY and is stronger than the notion of positive quadrant dependence. In this paper we consider the problem of testing for independence against the alternative thatY is RTI inX. We propose two distribution-free tests and obtain their limiting null distributions. The proposed tests are compared to Kendall's and Spearman's tests in terms of Pitman asymptotic relative efficiency. We have also conducted a Monte Carlo study to compare the powers of these tests.Research supported by an NSERC Canada operating grant at the University of Alberta.Part of this research was done while visiting the University of Alberta supported by the NSERC Canada grant of the first author. 相似文献
11.
Tim Futing Liao 《Quality and Quantity》1995,29(1):87-110
On social surveysdon't knows are a common answer to attitudinal questions, which often have binary or ordinal response categories.Don't knows can be nonrandomly selected according to certain demographic or socioeconomic characteristics of the respondent. To model the sample selection and correct for its bias, this paper discusses two types of bivariate models —binary-probit and the ordinal probit model with sample selection. The difference between parameter estimates and predicted probabilities from the analysis modelling the sample selection bias ofdon't knows and those from the analysis not modellingdon't knows is emphasized. Two empirical examples using the 1989 General Social Survey data demonstrate the necessity to correct for the bias in the nonrandom selection ofdon't knows for binary and ordinal attitudinal response variables. A replication of the analyses using the 1990 and 1991 General Social Survey data helps demonstrate the reliability of the sample selection bias ofdon't knows. 相似文献
12.
Anna Gottard 《Metrika》2007,66(3):269-287
Graphical models use graphs to represent conditional independence relationships among random variables of a multivariate probability
distribution. This paper introduces a new kind of chain graph models in which nodes also represent marked point processes.
This is relevant to the analysis of event history data, i.e. data consisting of random sequences of events or time durations of states. Survival analysis and duration models
are particular cases. This article considers the case of two marked point processes. The idea consists of representing a whole
process by a single node and a conditional independence statement by a lack of connection. We refer to the resulting models
as graphical duration models. 相似文献
13.
Several empirical studies have documented that the signs of excess stock returns are, to some extent, predictable. In this paper, we consider the predictive ability of the binary dependent dynamic probit model in predicting the direction of monthly excess stock returns. The recession forecast obtained from the model for a binary recession indicator appears to be the most useful predictive variable, and once it is employed, the sign of the excess return is predictable in-sample. The new dynamic “error correction” probit model proposed in the paper yields better out-of-sample sign forecasts, with the resulting average trading returns being higher than those of either the buy-and-hold strategy or trading rules based on ARMAX models. 相似文献
14.
This paper estimates simultaneously the supply and the demand determinants of the trademark adoption decision made by start-ups. We use a partial observability econometric model, as non-adoption is unobserved. Estimation is by maximum likelihood using the partial observability bivariate probit (POBP) model for an unbalanced longitudinal panel of surviving US start-ups (2004–2011). Our model is shown to provide a good explanation of supply and demand determinants of trademark adoption. For example, size, incorporation and expenditure on R&D are important on the supply side; and copyrights, licensing out and being in a high knowledge information sector are important on the demand side. 相似文献
15.
In this paper we develop a dynamic discrete-time bivariate probit model, in which the conditions for Granger non-causality can be represented and tested. The conditions for simultaneous independence are also worked out. The model is extended in order to allow for covariates, representing individual as well as time heterogeneity. The proposed model can be estimated by Maximum Likelihood. Granger non-causality and simultaneous independence can be tested by Likelihood Ratio or Wald tests. A specialized version of the model, aimed at testing Granger non-causality with bivariate discrete-time survival data is also discussed. The proposed tests are illustrated in two empirical applications. 相似文献
16.
Steffen Unkel 《Metrika》2017,80(3):351-362
In shared frailty models for bivariate survival data the frailty is identifiable through the cross-ratio function (CRF), which provides a convenient measure of association for correlated survival variables. The CRF may be used to compare patterns of dependence across models and data sets. We explore the shape of the CRF for the families of one-sided truncated normal and folded normal frailty distributions. 相似文献
17.
In this paper we propose estimators for the regression coefficients in censored duration models which are distribution free, impose no parametric specification on the baseline hazard function, and can accommodate general forms of censoring. The estimators are shown to have desirable asymptotic properties and Monte Carlo simulations demonstrate good finite sample performance. Among the data features the new estimators can accommodate are covariate-dependent censoring, double censoring, and fixed (individual or group specific) effects. We also examine the behavior of the estimator in an empirical illustration. 相似文献
18.
Summary Bivariate distributions, which may be of special relevance to the lifetimes of two components of a system, are derived using the following approach. As the two components are part of one system and therefore exposed to similar conditions of service, there will be similarity between their lifetimes that is not shared by components belonging to different systems. The lifetime distribution for a given system is assumed to be Gamma in form (this includes the exponential as a special case; extension to the Stacey distribution, which includes the Weibull distribution, is straightforward). The scale parameter of this distribution is itself a random variable, with a Gamma distribution. We thus obtain what might be termed a compound Gamma-Gamma bivariate distribution. The cumulative distribution function of this may be expressed in terms of one of the double hypergeometric functions of Appell.Generalised hypergeometric functions play an important part in this paper, and one of Saran's triple hypergeometric functions is obtained when generalising the above model to permit the scale parameters of the distributions for the two components to be correlated, rather than identical.Work started while the author was with the Transport Studies Group, University College London. 相似文献
19.
20.
《International Journal of Forecasting》2014,30(4):898-917
In this paper we propose a composite indicator for real-time recession forecasting based on alternative dynamic probit models. For this purpose, we use a large set of monthly macroeconomic and financial leading indicators from the German and US economies. Alternative dynamic probit regressions are specified through automated general-to-specific and specific-to-general lag selection procedures on the basis of slightly different initial sets. The resulting recession probability forecasts are then combined in order to decrease the volatility of the forecast errors and increase their forecasting accuracy. This procedure features not only good in-sample forecast statistics, but also good out-of-sample performances, as is illustrated using a real-time evaluation exercise. 相似文献