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Research background: Numerous modern indicators are attempting to integrate better economic, political, social, and environmental ambitions to uncover potential synergy, trade-offs, and future views that center around the notion of a so-called green economy. As long as the various indicators are not bounded in one comprehensive measurement, utilizing knowledge of relevant information and statistics that are crucial for monitoring the progress will not give us answers on the progress towards green growth either. Without an adequate measurement framework and robust statistics, the evaluation of the green economy is open to subjective reasoning. Purpose of the article: This paper aims to offer a strong standpoint for green topics by exploring the concept of Green GDP. The paper introduces a new, updated database on Green GDP for the set of 160 countries from 1970?2019. Methods: This database is distinctive due to its balanced coverage of two components of the green economy: quantitative feature (standard methodological algorithm) and qualitative feature (opportunity costs) within a common Green GDP accounting framework.    Findings & value added: Standardizing new methodologies and procedures for estimating environmental costs with a statistical foundation provides added value, which we hope will support the creation of reliable accounting and valuation systems for the green economy on a developing "green platform."

This article summarizes the main findings on problems related to the measurement and identification of business cycles. The aim of this study is to define and identify the determinants of business cycles. This paper provides an overview of the methodology and its future course. Our investigation suggests that some methodological frameworks are available in the literature, but none is perfect. A new development in the field lies in spectral analysis methods for measuring business cycles, which may have advantages over existing methodologies (nonlinearity, stationarity issues). We feel that fractional integration is important in the proper monitoring and explanation of business cycles. Spectral analysis techniques have also proved to be useful for addressing the problems of stationarity and structural breaks in time series when analyzing business cycles. Another important issue that is excluded when studying business cycles is that the link between cycles and economic growth is presumed to be non-existent, implying money neutrality. business cycles. Before this work, classical economists had denied the existence of business cycles. Classical

The general characteristics of output fluctuations in Croatia are examined under fractional integration framework. This paper evaluate the existence of long memory in real output decomposing fluctuations to transitory and permanent components. The results suggest that Croatian real output series behavior is best identified as ARFIMA model with order of integration 0.5 < d <1.5. This suggests that macroeconomic shocks in real output are highly persistent. Unlike other studies in Croatia that find real output to be I(0) or I(1) variable, test results from this study indicate that real output show the characteristics of long memory with mean reversion (fractional integration). ARTICLE INFO