On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing.Data mining, Official data, Intelligent data control system

Risk management, signal processing and econometrics: A new tool for forecasting the risk of disease outbreaks

This paper takes a novel approach for forecasting the risk of disease emergence by combining risk management, signal processing and econometrics to develop a new forecasting approach. We propose quantifying risk using the Value at Risk criterion and then propose a two staged model based on Multivariate Singular Spectrum Analysis and Quantile Regression (MSSA-QR model). The proposed risk measure (PLVaR) and forecasting model (MSSA-QR) is used to forecast the worst cases of waterborne disease outbreaks in 22 European and North American countries based on socio-economic and environmental indica- tors. The results show that the proposed method perfectly forecasts the worst case scenario for less com- mon waterborne diseases whilst the forecasting of more common diseases requires more socio-economic and environmental indicators

Reviewing role of Corporate governance regarding transactions with related parties and company performance among companies admitted into Tehran Stock Exchange

This research reviews the role of corporate governance regarding transactions with related parties and company performance. 85 companies admitted into the TSE were studies during a six months period between 2008 and 2013. Transaction with related parties is a usual trait of commercial activities. For example, some businesses conduct their activities via subsidiary businesses, particular partnerships and related businesses. Transactions with related parties can affect financial situation, financial performance and flexibility of the business. In this research the ratio of non-executive members of the board of directors to total members, membership or non membership of the managing director in the board, size of board and shares of institutional owners have been used as corporate governance variables. Finally, Eviews and Excel software and multi variable regression were used to test the research hypothesis. Results indicate a significant correlation between transactions with related parties and returns on assets. Results also showed that by importing corporate governance variables into the model, explanatory power of model increases and negative effect of transactions with related parties on performance reduces

The ENSO cycle and forecastability of global inflation and output growth : evidence from standard and mixed-frequency multivariate singular spectrum analyses

DATA AVAILABILITY STATEMENT : The data that support the findings of this study are available from the corresponding author upon reasonable request.In this paper, the role of the El Niño-Southern Oscillation (ENSO), measured by the Equatorial Southern Oscillation Index (EQSOI), is used to formally forecast the inflation and GDP growth rates of the United States, advanced (excluding the United States) and emerging countries, as well as the world economy (barring the United States). We rely on univariate and multivariate singular spectrum analyses (SSA), as well as mixed-frequency version of the latter since the EQSOI is monthly, while GDP is available only at quarterly frequency unlike monthly inflation rates. We find statistically significant evidence of the ability of the EQSOI in forecasting inflation and GDP growth rates of the four economic blocs, though there are exceptions in terms of forecasting gains associated with inflation rate of emerging economies and the growth rate of the United States. Our results have important implications for policymakers.http://wileyonlinelibrary.com/journal/forhj2023Economic

Does inequality really matter in forecasting real housing returns of the United Kingdom?

In this paper, we analyze the potential role of growth in inequality for forecasting real housing returns of the United Kingdom. In our forecasting exercise, we use linear and nonlinear models, as well as measures of absolute and relative consumption and income inequalities at quarterly frequency over the period 1975–2016. Our results indicate that, while nonlinearity in the data generating process of real housing returns is important, growth in inequality does not necessarily carry important information in forecasting the future path of housing prices in the United Kingdom.http://www.elsevier.com/locate/intecohj2019Economic

On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing

On the Application of Data Mining to Official Data

Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction to applications of DM to official statistics and flag the important issues and challenges. Considering recent advancements in software projects for DM, we propose intelligent data control system design and specifications as an example of DM application in official data processing

Historical forecasting of interest rate mean and volatility of the United States : is there a role of uncertainty?

Uncertainty is known to have negative impact on financial markets through its effects on investors’ decisions. In the wake of the “Great Recession”, quite a few recent studies have highlighted the role of uncertainty in predicting in-sample movements of interest rates. Since in-sample predictability does not guarantee out-of-sample forecasting gains, in this paper, we used historical daily and monthly data for the US to forecast mean and volatility of interest rate. The results show that changes in uncertainty measure movements fail to add any significant statistical gains to the forecast of interest rates for the US. In other words, policy makers in the US are not likely to improve their accuracy of future movements of the policy rate’s mean and volatility by incorporating information derived from changes in metrics of uncertainty.http://www.worldscientific.com/worldscinet/afe2021-12-01hj2021Economic