We develop a new method for deriving high-frequency synthetic distributions of consumption, income, and wealth. Modern theories of macroeconomic dynamics identify the joint distribution of consumption, income, and wealth as a key determinant of aggregate dynamics. Our novel method allows us to...

Purpose - Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the...

Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance....

Contrary to claims in studies on financial economics, a sparse database often obscures the identification of parameters in macroeconomic models. These identification problems originate from the poorly defined mapping between a structural model and reduced-form parameters. Hence, researchers rely...

Due to the rapid growth of the Chinese housing market over the past ten years, forecasting home prices has become a crucial issue for investors and authorities alike. In this research, utilising Bayesian optimisations and cross validation, we investigate Gaussian process regressions across...

This paper analyses the impact of various macroeconomic shocks - including aggregate demand, supply, monetary policy, real exchange rate, and budget deficit deviation shocks - on Romania's economy using a VAR model with Bayesian inference. The study captures the period following the adoption of...

Accurately detecting anomalous points in time-series data is critical, as false positives can mislead business stakeholders, waste valuable resources, and diminish the overall impact of the detection system. While various statistical and machine learning techniques are employed to flag potential...

Forecast risk management is central to the financial management process. This study aims to apply Monte Carlo simulation to solve three classic probabilistic paradoxes and discuss their implementation in corporate financial management. The article presents Monte Carlo simulation as an advanced...

COVID-19's effects on mortality are hard to quantify. Issues with attribution can cause problems with resulting conclusions. Analyzing excess mortality addresses this concern and allows for the analysis of broader effects of the pandemic. We propose separate ARIMA models to analyze excess...

Impulse response functions (IRFs) are crucial for analyzing the dynamic interactions of macroeconomic variables in vector autoregressive (VAR) models. However, traditional IRF estimation methods often have limitations with assumptions on variable ordering and restrictive identification...

We propose a flexible, extensible family of distributions for testing Markov Chain Monte Carlo implementations. Distributions are created by nesting simple transformations, which allow various shapes, including multiple modes and fat tails. The resulting distributions can be sampled with high...

This paper investigates the heterogeneity of inflation expectations among households, firms, and professionals across 14 economies. Using Bayesian model averaging and panel data regressions, we identify key determinants of inflation expectations, assess their stability over time, and evaluate...

Handling uncertainty is a key aspect of production management. This paper employs a Bayesian network (BN) approach to improve uncertainty analysis in production decision-making by identifying common causal factors that may affect one or more components of an integrated supply chain problem. A...

This paper is the first to meta-analyse the literature on the causal effects of school-meal programmes on children's behavioural, health and educational outcomes in developed countries, while addressing potential publication bias and heterogeneity between studies. We create a sample of 2,821...

This paper estimates the fiscal multipliers of green public spending using a linear Bayesian Panel VAR and a Smooth Transition VAR framework, with quarterly data for the period 1995Q1-2022Q4 for EU member states. We group EU member states based on similar- ities in debt trajectories and green...

Electricity price forecasting has been a topic of significant interest since the deregulation of electricity markets worldwide. The New Zealand electricity market is run primarily on renewable fuels, and so weather metrics have a significant impact on electricity price and volatility. In this...

We analyse the accuracy of an econometric model for nowcasting GDP growth in a true real-time setting. The analysis is based on a unique sample of nowcasts that were produced in real time and stored. Our results support the use of econometric models for nowcasting because the accuracy of these...

Youth unemployment has remained one of the major social and economic problems facing many African countries despite persistent efforts by governments and other stakeholders to mitigate the problem. We deployed a two-parameter beta geospatial model within a distributional regression framework...

We present alternative methods for calculating and interpreting the influence of exogenous shocks on historical episodes within the context of DSGE models. We show analytically why different methods for calculating shock decompositions can generate conflicting interpretations of the same...

Business cycles are often regarded as aggregate phenomena. However, against the backdrop of rapid structural transformation in Chinese economy, they are also influenced by cyclical changes in various sectors and the evolution of the economic network structure. From the perspective of production...

Estimates of the area- and household idiosyncratic error distributions from household income and consumption regression models across 142 household surveys from 16 different countries, the type of models that underpin poverty maps, points to significant deviations from normality. Accounting for...

The rapid evolution of digital transformation necessitates a comprehensive understanding of national digital readiness. The Network Readiness Index (NRI) serves as a key benchmark for assessing a country's preparedness to leverage digital technologies for economic and societal development. This...

Standard methods for constructing error bands around impulse response functions consider them in isolation, neglecting the estimation uncertainty that arises across variables and time horizons due to the joint nature of the underlying structural parameters. For example, one approach to assessing...