This article introduces the R package ExtremeBounds to perform extreme bounds analysis (EBA), a sensitivity test that examines how robustly the dependent variable of a regression model is related to a variety of possible determinants. ExtremeBounds supports Leamer's EBA that focuses on the upper...

Recreational services are demanded because they generate benefits. The recreational benefits connected with a destination can be valued based on visitor preferences, which can aid in the formulation of an appropriate Natural Resource Management policy. Environmental and natural resource...

The objective of this paper is to examine the impact of demutualization upon the performance of stock exchanges' in terms of their liquidity as per the share turnover velocity and the returns that are generated from the broad indexes. The impact of demutualization has been examined upon a global...

Estimation of empirical relationships is prone to bias. Economists have carefully identified and addressed sources of bias in structural and quasi-experimental approaches, but the randomized control trial (RCT) has only recently begun to receive such scrutiny. In this paper, we argue that...

Vector error-correction models (VECM) are increasingly being used to capture dynamic relationships between financial variables. Estimation and interpretation of such models can be enhanced if zero restrictions are allowed in the coefficient matrices. Specifically, in tests of indirect causality...

We introduce a data driven and model free approach for computing conditional expectations. The new method is based on classical techniques combined with machine learning methods. In particular, we consider kernel density estimation based on simulated risk factors combined with a control variate....

We estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps are detected in both the transaction price (observation equation) and fundamental value (state equation). The model's parameters and variances are updated in real time. Prices...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

This paper introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non-Gaussian Ornstein-Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented. Further we study the...

We construct a Malmquist productivity index based on stochastic non-parametric envelopment of data (StoNED) method, and we study how the distributional assumptions in the second StoNED stage affect productivity change and its decompositions. Our discussion show that the distributional...