In today’s technology-driven world-economy, banking-services have been modernized where customers compete for comparative time-saving-options. Bangladesh, a developing country, is no exception. Besides traditional banking, Agent-banking, bKash, Western-Union etc. serve new-way...

This is an introductory article which explains the importance of explicit consideration and modeling of causality, contrary to current econometric practice, in order to use data set for extraction of meaningful information. One of the easiest to understand approaches to causality is via...

As a contribution toward the ongoing discussion about the use and mis-use of p-values, numerical examples are presented demonstrating that a p-value can, as a practical matter, give you a really different answer than the one that you want.

We propose novel nonparametric estimators for stochastic volatility and the volatility of volatility. In doing so, we relax the assumption of a constant volatility of volatility and therefore, we allow the volatility of volatility to vary over time. Our methods are exceedingly simple and far...

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...

Both stochastic dominance and Omegaratio can be used to examine whether the market is efficient, whether there is any arbitrage opportunity in the market and whether there is any anomaly in the market. In this paper, we first study the relationship between stochastic dominance and the Omega...

Group identification refers to the problem of classifying individuals into groups (e.g., racial or ethnic classification). We consider a multinary group identification model where memberships to three or more groups are simultaneously determined based on individual opinions on who belong to what...

We experimentally study how people form predictive models of simple data generating processes (DGPs), by showing subjects data sets and asking them to predict future outputs. We find that subjects: (i) often fail to predict in this task, indicating a failure to form a model, (ii) often cannot...