Binary misclassification and identification in regression models

We study a regression model with a binary explanatory variable that is subject to misclassification errors. The regression coefficient is then only partially identified. We derive several results that relate different assumptions about the misclassification probabilities and the conditional variances to the size of the identified set.     

Estimation of relative average treatment effects with misclassification

This paper identifies and estimates the relative average treatment effect in the presence of misclassification. We propose consistent estimators based on nonparametric methods. The simulation results reported illustrate the performance of the proposed estimators.     

An alternative identification of nonlinear dynamic panel data models with unobserved covariates

I provide the nonparametric identification of nonlinear dynamic panel data models. I relax the assumption of covariate evolution in Shiu and Hu (2013) by the results of Hu and Shum (2012). The assumptions include first-order Markov assumptions and a restriction on the evolution of the covariate.     

Nonparametric lag selection for nonlinear additive autoregressive models

The lag selection procedure based on the final prediction error (FPE) is investigated when the additive structure is a priori known in the nonparametric autoregression. The consistency of the lag selection is proved, followed by the finite sample simulation results.     

An OLS approach to computing Ramsey equilibria in medium-scale macroeconomic models

This note describes a general procedure for solving for the steady state and the dynamics implied by the Ramsey equilibrium of medium-scale macroeconomic models. The procedure yields an exact numerical solution for the steady state and second-order accurate dynamics. It introduces a novel projection-based approach to calculating exact solutions to the steady state of Ramsey equilibria.     

Efficient estimation of partially linear varying coefficient models

In this paper, we consider the problem of estimating a semiparametric partially linear varying coefficient model. We derive the semiparametric efficiency bound for the asymptotic variance of the finite-dimensional parameter estimator. We also propose an efficient estimator for estimating the finite-dimensional parameter of the model. Simulation results show substantial efficiency gain of our proposed estimator over a conventional estimator as considered in Ahmad et al. (2005).     

Lagged duration dependence in mixed proportional hazard models

We study the identification of a mixed proportional hazard model with lagged duration dependence when data provide multiple outcomes per stratum. Within strata variation is exploited to non-parametrically identify lagged duration dependence in more general models than in the literature.     

Partial identification in binary response models with nonignorable nonresponses

This study investigates the identification of parameters in semiparametric binary response models of the form y=1(x^′β+v+ε>0)$y=1(x^{\prime }\beta +v+\epsilon >0)$ when there are nonignorable nonresponses. We propose an estimation procedure for the identified set, the set of parameters that are observationally indistinguishable from the true value β$\beta$, based on the special regressor approach of Lewbel (2000). We show that the estimator for the identified set is consistent in the Hausdorff metric.     

An improved generalized moments estimator for a spatial moving average error model

Following Arnold and Wied (2010), we suggest an improved generalized moments estimator for the spatial moving average error model which takes explicitly into account that the moment conditions are based on OLS residuals rather than the true disturbances.     

Semiparametric binary random effects models: Estimating two types of drinking behavior

I propose a new estimator for cross-section semiparametric regressions containing unobserved binary random effects and apply it to alcohol consumption. The random effects (health consciousness) explain a significant proportion of otherwise unexplained variation in alcohol consumption. Education positively correlates with health consciousness.     

An Improved Two‐step Regularization Scheme for Spot Volatility Estimation

We are concerned with the problem of spot volatility estimation in the presence of microstructure noise. We introduce an estimator based on the technique of multi‐step regularization. A preliminary form for such an estimator was proposed in Ogawa (2008) and was shown to work in a real‐time manner. However, the main drawback of this scheme is that it needs a lot of observation data. The aim of the present paper is to introduce an improvement to this scheme, such that the modified estimator can work more efficiently and with a data set of smaller size. The technical aspects of implementation of the proposed scheme and its performance on simulated data are analysed. The scheme is tested against other spot volatility estimators, namely a realized volatility type estimator, the Fourier estimator and three kernel estimators.     

Property rights and investments: An evolutionary approach

When contracts are not enforceable, or property rights are not clearly defined, individuals may lack an incentive to carry out costly investments even when they are socially efficient. Some recent contributions such as Ellingsen and Robles (2002) prove that this problem may be less dramatic than standard economic models would suggest. They propose evolutionary models in which only efficient equilibria can be (stochastically) stable. In this paper we show that these results are not robust with respect to the introduction of individual heterogeneity. When individuals have different cost functions, stochastically stable states may be inefficient, even when they induce a positive (suboptimal) level of investment.     

Bidirectional technological spillover in the Chinese star-rated hotel sector: An empirical investigation

The star-rated hotel sector has played an increasing role in Chinese economic development. A feature of this sector is the technology-gap between high- and low-end hotels, which may generate spillover through different channels: such as human capital mobility and management systems. High-end hotels are technological leaders with better access to technology, foreign connections, and government policy support, while low-end hotels have better localized knowledge and expertise. Therefore, it is important to see whether there is spillover between high- and low-end hotels. Two contributions of our paper are to model hotels as multi-service decision-makers, and to rely on a nonparametric empirical strategy. The results show that high-end hotels are the major spillover generators moving the star-rated hotel sector to better performance. On the other hand, low-end hotels not only integrate the technological knowledge from high-end hotels, but also share their experience of local knowledge.     

An Afriat Theorem for the collective model of household consumption

We provide a nonparametric ‘revealed preference’ characterization of rational household behavior in terms of the collective consumption model, while accounting for general individual preferences that can be non-convex. Our main result is the Collective Afriat Theorem, which parallels the well-known Afriat Theorem for the unitary model. First, it provides a characterization of collectively rational consumption behavior in terms of collective Afriat inequalities. Next, it implies the Collective Axiom of Revealed Preference (CARP) as a testable necessary and sufficient condition for data consistency with collective rationality. Finally, the theorem has some interesting testability implications. With only a finite set of observations, the nature of consumption externalities (positive or negative) in the intra-household allocation process is non-testable. The same non-testability conclusion holds for privateness (with or without externalities) or publicness of consumption. By contrast, concavity of individual utility functions (representing convex preferences) turns out to be testable. In addition, monotonicity is testable for the model that assumes all household consumption is public.     

A new estimator for trade costs and its small sample properties

This paper discusses the estimation of parameters of a traditional transportation model, as it is typically present in so-called Takayama–Judge type spatial price equilibrium models. In contrast to previously used estimation methods, observations of regional prices as well as of trade costs are used in a direct estimation of the first order conditions. The proposed method uses bi-level programming techniques to minimize a weighted least squares criterion under the restriction that the estimated parameters satisfy the Kuhn–Tucker conditions for an optimal solution of the transport model. A penalty function and a smooth reformulation are used to iteratively approximate the complementary slackness conditions. Monte-Carlo simulations are used to trace out some properties of the estimator and compare it with a traditional calibration method. The analysis shows that the proposed technique estimates prices as well as trade costs more precisely than the traditional calibration method. It is suggested to apply the same method to a range of linear and quadratic models.     

Testing for structural breaks with local smoothers: A simulation study

By means of an extensive Monte Carlo simulation study based on the design of Chen and Hong (2012) we compare the performance of the tests they proposed for parameter stability with the linearity test of Li et al. (2002) and the functional form test of Li and Wang (1998). We find that the test of Li et al. (2002) test adapted to testing for parameter stability performs favorably well in terms of size and equally well in terms of power compared with the others, whereas the test by Li and Wang has no power.     

Iterative algorithm for non parametric estimation of the instrumental variables quantiles

This paper proposes a simple algorithm for the numerical computation of the non parametric IV quantile estimation. This algorithm is based on the Landweber iterations for solving a nonlinear integral equation. The paper is illustrated by numerical simulations.     

A nonparametric test for path dependence in discrete panel data

This paper proposes a test for path dependence in discrete panel data based on a characterization of stochastic processes that are mixtures of Markov chains. This test is applied to European Community Household Panel data on employment histories. The data allow to reject the null of no path dependence in all subsamples considered.     

Overnight exchange rate risk based on multi-quantile and joint-shock CAViaR models

Overnight risk of exchange rate is more and more important because the exchange rate trading time of various countries is inconsistent. Drawing on the multi-quantile CAViaR model for two markets, this study proposes a multi-quantile CAViaR model for three markets and a multi-quantile CAViaR model for joint shock. The two new models are used to measure the impact of the U.S. Dollar index and the Euro on the overnight risk for the exchange rate of the Japanese Yen, Hong Kong Dollar, and Chinese Renminbi. The results show that, first, a lag risk affects the overnight risk of the three exchange rates, of which the Renminbi exchange rate is subject to the largest risk. Second, the U.S. Dollar index and Euro exchange rate risks impact the overnight risk of the three exchange rates and this effect is highest for the overnight risk of the Yen's exchange rate. In addition, the impact of the U.S.Dollar index risk is greater than that of the Euro. Third, the Euro and U.S.Dollar index produce a joint shock on the overnight risk of the three exchange rates, and here, the Yen's exchange rate suffers the biggest shock. Finally, the multi-quantile CAViaR model for joint shock is more accurate than that for three markets, particularly when the Hong Kong Dollar exchange rate has a 5% VaR. These empirical results have meaningful implications for regulatory authorities.     

Innovation and duration of exports

This paper uses survival analysis to investigate the effect of innovation on export duration of 105 countries at the product level. The estimation shows that the duration of exports increases with innovation. The effect is stronger for differentiated products than for homogeneous products. The estimates are consistent with the quality ladder model.