The economy of Pakistan has been facing instability and downward trends due to several factors, such as rising foreign debt and goods and services prices. The regression and ARDL models are applied by using R software. Adding lag values of variables become necessary to measure the long-run...

Biased responses in survey studies could seriously harm and mislead our economic decision-making. To mitigate survey response bias, we suggest an alternative way of combining two existing strategies, cheap talk and the Bayesian Truth Serum (BTS). In our three proof-of-concept experiments, we...

We study a hierarchical Bayesian persuasion game with a sender, a receiver, and several potential intermediaries, generalizing the framework of Kamenica and Gentzkow (2011). The sender must be persuasive through a hierarchy of intermediaries to reach the final receiver, whose action affects all...

We propose a mixed‑frequency regression prediction approach that models a time‑varying trend, stochastic volatility and fat tails in the variable of interest. The coefficients of high‑frequency indicators are regularised via a shrinkage prior that accounts for the grouping structure and...

The paper solves the optimal sampling problem of a decision-maker that wants to predict a target variable. We prove the existence of complementarities between the sample size and the number of explanatory variables in a data set. We show that the optimal dimensions of the data set reflect the...

How do you make inferences from a Bayesian network (BN) model with missing information? For example, we may not have priors for some variables or may not have conditionals for some states of the parent variables. It is well-known that the Dempster-Shafer (D-S) belief function theory is a...

We examine how financial crises redistribute risk, employing novel empirical methods and micro data from the largest financial crisis of the 20th century – the Great Depression. Using balance-sheet and systemic risk measures at the bank level, we build an econometric model with incidental...

In spatio-temporal epidemiological analysis, it is of critical importance to identify the significant covariates and estimate the associated time-varying effects on the health outcome. Due to the heterogeneity of spatio-temporal data, the subsets of important covariates may vary across space and...

Little is known about how gamblers estimate probabilities from multiple information sources. This paper reports on a preregistered study that administered an incentivized Bayesian choice task to n=465 participants (self-reported gamblers and non-gamblers). Our data failed to support our main...