This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally....

We consider a general class of observation-driven models with exogenous regressors for double bounded data that are based on the beta distribution. We obtain a stationary and ergodic beta observation-driven process subject to a contraction condition on the stochastic dynamic model equation. We...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimates are moments...

Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q r. The present paper studies...

Models of simultaneous discrete choice may be incomplete, delivering multiple values of out- comes at certain values of the latent variables and covariates, and incoherent, delivering no val- ues. Alternative approaches to accommodating incompleteness and incoherence are considered in a unifying...

Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance...

The neutral band is the interval where deviations from Covered Interest Parity (CIP) are not considered meaningful arbitrage opportunities. The band is determined by transaction costs and risk associated to arbitrage. Seemingly large deviations from CIP in the foreign exchange markets for the US...

We assess the role of measurement error in minimum wage evaluations when the treatment variable - the bite - is inferred from a survey wage distribution. We conduct Monte Carlo experiments on both simulated and empirical distributions of measurement error derived from a record linkage of survey...

We consider a situation where the sample design of a survey is modified over time in order to save resources. The former design is a classical large-scale survey. The new design is a mixed mode survey where a smaller classical sample is augmented by records of an online survey. For the online...

This paper analyzes the problem of weak instruments on identification, estimation, and inference in a simple nonparametric model of a triangular system. The paper derives a necessary and sufficient rank condition for identification, based on which weak identification is established. Then...

In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market components that we consider important to the modeling...

We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010-2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among...

In this paper, we propose a general family of Birnbaum–Saunders autoregressive conditional duration (BS-ACD) models based on generalized Birnbaum-Saunders (GBS) distributions, denoted by GBS-ACD. We further generalize these GBS-ACD models by using a Box-Cox transformation with a shape...

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact in the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between...

This paper reviews some key contributions to econometric analysis of human fertility in the last 20 years, with special focus on discussion of prevailing econometric modeling strategies. We focus on the literature that highlights the role of the key drivers of the birth outcomes, including age...

This study investigates the effectiveness of six of the key international indices in estimating Saudi financial market (TADAWUL) index (TASI) movement. To investigate the relationship between TASI and other variables, six equations were built using two independent variables of time and...

In proxy vector autoregressive models, the structural shocks of interest are identified by an instrument. Although heteroskedasticity is occasionally allowed for, it is typically taken for granted that the impact effects of the structural shocks are time-invariant despite the change in their...

This paper reviews some key contributions to econometric analysis of human fertility in the last 20 years, with special focus on discussion of prevailing econometric modeling strategies. We focus on the literature that highlights the role of the key drivers of the birth outcomes, including age...

In an important class of econometric problems, researchers select a target parameter by maximizing the Euclidean norm of a data-dependent vector. Examples that can be cast into this frame include threshold regression models with estimated thresholds and structural break models with estimated...

We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model,...

Because the use of p-values in statistical inference often involves the rejection of a hypothesis on the basis of a number that itself assumes the hypothesis to be true, many in the scientific community argue that inference should instead be based on the hypothesis' actual probability...

We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...

In this paper, we systematically analyze the empirical importance of standard conditions for the validity and generalizability of field experiments: the internal and external overlap and unconfoundedness conditions. We experimentally varied the degree of overlap in disjoint sub-samples from a...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

This study develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed effects, allowing for temporal correlation within each individual. The conventional QR standard errors can seriously underestimate the uncertainty of estimators and, therefore,...

This chapter reviews the microeconometrics literature on partial identification, focusing on the developments of the last thirty years. The topics presented illustrate that the available data combined with credible maintained assumptions may yield much information about a parameter of interest,...

In conventional structural vector autoregressive (VAR) models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. However, even if there is...