Methodical approaches to forecasting and early detection of economic cyclicity

The analysis and generalization of theoretical preconditions of formation of the advancing economic indicators which at different times in different countries of the world are used as indicators of change of a phase of an economic cycle is carried out. Based on the analysis of literature sources, it is established that the methodology of economic forecasting of cyclicality in the scientific literature includes two main areas, namely: a) direct forecasting of the dynamics of key macroeconomic indicators based on extrapolation, correlation and regression analysis, expert surveys (consensus forecasts) and surveys of economic entities; b) the use of leading economic indicators, which by their nature can be pro-cyclical, counter-cyclical and acyclical, and in relation to the phase of the economic cycle - ahead, late and synchronous. The most common leading indicators are considered, among which the Index of leading economic indicators of the USA, Composite leading index of the Organization for Economic Cooperation and Development (OECD), Indicator of business confidence by types of economic activity, consumer confidence, business climate and economic sentiment in accordance with the Special Data Dissemination Standard of the International Monetary Fund. Since 2006, the National Bank of Ukraine has been conducting a survey on the status and prospects of business activity, and similar quarterly indicators have been developed by the State Statistics Service of Ukraine and implemented since 2013. At the same time, a separate indicator is proposed for forecasting business activity in construction - the indicator of business confidence in construction (IDVB). However, the feasibility of using these indicators has yet to be proven in practice. To increase the accuracy of forecasting changes in the phases of economic cycles, it is proposed to develop separate indicators at the sectoral and regional levels. Theoretical generalization and substantiation of causes, consequences, methods of counteracting economic cyclicality should become the basis for further applied research. This approach is a theoretical basis for the development of tools for countercyclical management of enterprises, sectors of the economy and national economies in conditions of fluctuations in business activity.

Algorithmic Foundations of Economic and Mathematical Modeling of Network Logistics Processes

Nowadays, digitizing the data stream is enabling the evolution of logistics processes. The data-driven network logistics processes are evaluated by leading economic indicators. The purpose of this study is to further develop the algorithmic foundations of economic and mathematical modeling of logistics networks based on advanced technologies that the digitalization process provides. Methods of mathematical modeling of flows of various resources in logistic networks, the structure of which is presented in the form of a graph, are used in the work. The economic benefit lies in the implementation of the planning concept based on leading indicators. As a result, using a set of formalisms, a mathematical model has been developed, which will make it possible to search for optimal solutions based on the criterion of economic efficiency. The results obtained will find application not only in transport problems. Network logistics includes the transportation of liquid and gaseous materials through pipelines, energy through electrical networks. A universal mathematical model will allow the results to be applied in many industries and economic activities when it is required to make economically sound decisions based on a stream of digital data coming in real time.

US Consumer Confidence Responses to Shocks: COVID19 Scenarios and Recovery.Under review: REHO Special Issue

Personal consumption expenditure has long been a key driver of the US economy, accounting for roughly two-thirds of GDP. Consumer confidence is a significant predictor of consumer expenditure especially in times of shocks. The US has experienced many shocks since 1978; the latest of which is the outbreak of coronavirus. COVID19 has spread from China to the whole world; the pandemic has had far-reaching consequences for global political, social, economic, and financial structures. Consumer confidence is one of the leading economic indicators that provides information on the current and future path of the economy, helps in stimulating economic activity, and predicts change in macroeconomic variables, especially during times of economic and political uncertainty. Our study investigates the relationship between consumption expenditure and consumer confidence in the USA. It analyzes the US consumer confidence response to 11 different shocks since 1978, focusing on COVID-19 shock. Our investigation uses Michigan's monthly Consumer Sentiment Index (CSI) and its five components from January 1978 to April 2020. The paper is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios; by providing a projection until August 2021. The goal is to estimate the time needed for recovery and provide guidance to policymakers on ways to restore consumer confidence to tame the impact of coronavirus on effective demand. Under the two more optimistic scenarios we predict that recovery will begin by January 2021. Under the third, less optimistic, scenario we predict that recovery will begin by April 2021.

FORECASTING BANKS RETURN ON EQUITY USING LEADING ECONOMIC INDICATORS

The research examines an approach to forecast return on equity using leading economic indicators for short periods in banks. ROE is one of the most important ratios for performance measurement. Its adequacy is necessary for competitiveness, attract funding in financial markets, accumulate reserve for future turbulences, secure compliance with supervisory requirements and maintain positive signals for the market. There is still a debate in the literature on factors of commercial banks’ profitability forecasting, techniques, and most appropriate models to improve the correctness of predicting and acquiring more accurate signals for communication on targets. The problems are still relevant from both a theoretical perspective and practical implementation. This research aims to prove the necessity to include leading economic indicators for short term ROE forecasting. It conducts investigations for the relevant studies, using regression analysis, necessary tests, ascertains opportunities and limitations of using these indicators and develops a conceptual model and its assessment major Baltic banks. The results show verification of approach to forecast ROE using leading economic indicators for short periods. Such study complements signalling theory with a new approach, how to predict and acquire signal not only using economic indicators as a general group but sub-group them into coinciding, lagging and leading.

Construction of business confidence index based on a system of economic indicators

One of the important indicators that characterize the economy of the country is the business confidence index. It is the basis for tracking the cycles of economic dynamics and analysis of the country's business climate. Evaluation of this indicator makes it possible to predict the crisis phenomena that are occurring in the economy, and to develop possible ways out of difficult situations. On the example of the five countries (Ukraine, Germany, Hungary, Slovenia, Poland) it was also analyzed the possibility of constructing the business confidence index based on economic indicators, which characterize current economic activity of the country. For analysis, the quarterly values of economic indicators over the last years were taken. The selected economic indicators based on cross-correlation analysis were ranked into three groups: coincident, lagging and leading indicators. Using coincident and leading economic indicators, the several regression models of the business confidence index were built. On the basis of the obtained regression models, the forecast of business confidence index value for the next period is evaluated and the trends of its development are established.