Business Cycle Analysis Research Articles

Divisia monetary aggregates, monetary policy and business cycle analysis

Abstract The paper builds a parsimonious US business cycle SVARMA model, establishing identification conditions for independent monetary shocks. The SVARMA model, utilizing Divisia M3 and Divisia M4, is compared to the simple sum M2. The monetary rule with Divisia M3 yields theoretically consistent results marked by the absence of the usual price and liquidity puzzles. As the Federal Reserve (Fed) took a more hawkish approach to curb inflation, significant increases in US interest rates and declines in monetary aggregates were largely influenced by the Fed’s reaction function, which incorporates the Divisia M3 monetary rule. Findings emphasize the monetary impact on the business cycle, highlighting the significance of Divisia monetary aggregates. Historical and variance decompositions reveal diverse, dynamic effects of monetary shocks on macroeconomic variables. The SVARMA model with Divisia M3 and M4 demonstrates superior performance over simple sum M2 in capturing the time path of monetary shocks.

Analyzing Business Cycles in Azerbaijan: Application of Various Filters and Spectral Analysis

This study investigates the cyclical behavior of Azerbaijan's economy and its non-oil-gas sector through the application of various filtering techniques, including the Hodrick-Prescott, Baxter-King, and Christiano-Fitzgerald filters. Utilizing quarterly GDP data from Q1 2001 to Q4 2023, we analyze the volatility, cycle duration, and significant periods of economic growth and contractions. Our analysis reveals that the Hodrick-Prescott filter shows more pronounced and volatile cyclical components, while the Baxter-King and Christiano-Fitzgerald filters provide smoother and more moderated views. Spectral analysis, employing periodograms smoothed with Bartlett, Hamming, Hann, and Parzen kernel windows, identifies cycle durations ranging from 4.1 to 19.4 quarters for total GDP and 4.3 to 19.4 quarters for non-oil-gas GDP. We find that Azerbaijan's economy exhibits higher volatility compared to advanced economies, likely due to its dependence on oil exports and susceptibility to external shocks. Key periods such as the 2008 financial crisis and the COVID-19 pandemic significantly impacted economic performance, with notable declines identified across all filtering methods. The HP filter indicates a sharp and more prolonged downturn during these crises, whereas the BK and CF filters capture less prolonged and less severe impacts. This research provides a comprehensive understanding of Azerbaijan's business cycles, highlighting the importance of robust methodologies in economic analysis. Our findings contribute to the limited literature on Azerbaijan’s economy and offer valuable insights for policymakers aiming to enhance economic stability and growth.

Cycle Fluctuations in the U.S. Real GDP and National Income and Product Accounts Aggregates

This article provides a new set of empirical regularities describing the U.S. macroeconomy, focusing on business cycle fluctuations in the real GDP and eleven major aggregates from the U.S. National Income and Product Accounts (NIPAs). Patterns of the cyclical fluctuations are assessed using filtering methodologies that adapt to the properties of the series being studied. We employ a recent dataset that includes the Great Recession caused by the 2008 financial crisis and the ensuing recovery. We aim to (1) examine the lead-lag relations via cross-correlations between the aggregate cycle in the U.S. real GDP and the cyclical movements in the eleven major NIPA aggregates; (2) investigate econometrically the inter-linkage between the cyclical component of real GDP and that of each NIPA aggregate by way of the Granger-causality test; and (3) evaluate the capability or the predictive power of each NIPA aggregate to forecast real GDP growth via three forecasting models. Comparisons are made with popular nonparametric HP and Baxter-King (BK) filters. The basic conclusion from the empirical analysis is that the adaptive model-based filters have demonstrated advantages over the commonly used HP and BK filters for business cycle analysis across very diverse economic series from the U.S. national accounts, and the structural time series model using smoothed trend and cycle estimates produced more accurate forecasts than the AR(p) model that forecasts directly using the unfiltered time series.

Business-Cycle Analysis and Zero-Crossings of Time Series: A Generalized Forecast Approach

Business-Cycle Analysis and Zero-Crossings of Time Series: A Generalized Forecast Approach

Business cycle synchronization and asymmetry in the European Union

Measuring output gaps and assessing business cycle synchronization across countries can be an important research theme for an economic union. However, different empirical models can lead to very different inference about output gaps. We analyze business cycle movements and synchronization for all European Union members for the period 1975Q1–pre-COVID and 1975Q1–2022Q4. We account for model uncertainty by averaging across a set of output gap models both by using a Phillips Curve motivated weighted average and a simple average. Similarly, we compare several alternative synchronization measures. We find that, in contrast to the previous literature, both the estimated output gap and the level of synchronization depend on the individual empirical measure used. Our averaged gaps match recession dates well and suggest that many of the countries exhibit a high degree of business cycle nonlinearities. Finally, the core Eurozone countries are highly synchronized, but there are differences in synchronization outside the core.

Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context

Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context

The credit card-augmented Divisia monetary aggregates: an analysis based on recurrence plots and visual boundary recurrence plots

In this paper, we compare the dynamics of the growth rates of the original Divisia monetary aggregates, the credit card-augmented Divisia monetary aggregates, and the credit card-augmented Divisia inside monetary aggregates. This analysis is based on the methods of recurrence plots, recurrence quantification analysis, and visual boundary recurrence plots which are phase space methods designed to depict the underlying dynamics of the system under study. We identify the events that affected Divisia money growth and point out the differences among the different Divisia monetary aggregates based on the recurrence and visual boundary recurrence plots. We argue that the broad Divisia monetary aggregates could be used for monetary policy and business cycle analysis as they are exhibiting less fluctuation compared to the narrow Divisia monetary aggregates. They could positively affect policy decisions regarding environmental choices and sustainability. We also point out the changes in the monetary dynamics locating the 2008 global financial crisis and the Covid-19 pandemic.

The credit-augmented Divisia aggregates and the monetary business cycle

Abstract We follow Belongia and Ireland (2021) and investigate the role that the Center for Financial Stability credit card-augmented Divisia monetary aggregates could play in monetary policy and business cycle analysis. We use Bayesian methods to estimate a structural VAR under priors that reflect Keynesian channels of monetary transmission, but produce posterior distributions for the structural parameters consistent with classical channels. We also find that valuable information is contained in the credit-augmented Divisia monetary aggregates and that they perform even better than the conventional Divisia aggregates, in terms of highlighting the role of the money supply in aggregate demand.

Monetary policy and economic fluctuations

Abstract We assess the responses of output and inflation to monetary policy shocks in the context of a Bayesian, monetary structural vector autoregressive model. We allow money supply and leverage measures to enter into the interest rate policy rule and use an identification approach that is by construction devoid of any price puzzles. We provide a comprehensive comparison between monetary policy shocks under a policy regime that follows a standard Taylor rule and those that augment the standard reaction function of the central bank with measures of leverage and the money supply. We find that contractionary monetary policy is more pronounced and persistent when the reaction function of the central bank is augmented with measures of money and leverage than when the reaction function follows a typical Taylor rule. Our results support the use and inclusion of monetary aggregates in monetary policy and business cycle analysis.

Demand or Supply? An empirical exploration of the effects of climate change on the macroeconomy

Using an original panel data set for 24 OECD countries over the sample 1990–2019 and a multivariate empirical macroeconomic framework for business cycle analysis, the paper tests the combined macroeconomic effects of climate change, environmental policies and green innovation. Overall, we find evidence of significant macroeconomic effects over the business cycle: physical risks act as negative demand shocks while transition risks act as downward supply movements. The disruptive effects on the economy typical of a disorderly transition are exacerbated for low income, high emission countries with no history of environmental policy or with a high exposure to natural disasters. In general, one size does not fit all and results support the need for a (possibly country-specific) policy mix to counteract climate change with a balance between demand-pull and technology-push policies.

Dissecting the Moroccan business cycle: A trade-based identification of agricultural supply shocks

The consideration of the agricultural sector within the business cycle analysis is crucial for both diagnostic analysis and economic policy in developing countries. One of the critical issues is the identification of agricultural supply shocks. This paper introduces a novel approach to identify these shocks, based on the foreign trade of agricultural products. This contrasts with existing literature, which relies upon weather variables such as precipitation or temperature. Our approach is applied to dissect the business cycle in Morocco from 1999 to 2019, employing Structural Vector Autoregressive (SVAR) models identified by sign restrictions and exogeneity assumptions. Our framework has demonstrated its ability to replicate agricultural fluctuations in Morocco. In addition, our estimates indicate that agricultural supply shocks play a substantial role in output fluctuation (accounting for almost a third of its variability), but do not exert a significant effect on inflation, contrary to what is documented in other countries.

The Effects of Government Expenditure on the Output: A Real Business Cycle Analysis for the Romanian Economy

Abstract One of the most researched topics in macroeconomics is the development and implementation of Real Business Cycle models. This article presents a small Real Business Cycle model, which is built for the Romanian economy, with data from the 2nd quarter of 1995 through the 3rd quarter of 2022. The main aim of this analysis is to assess the historical influence of exogenous and government spending shocks on economic growth. In order to obtain accurate results, we implemented a Bayesian estimation technique for calculating the parameters of the model. The main findings indicate the significant exogenous shocks effect on the Romanian economy, and the way in which government spending had a positive effect on increasing economic growth for the period between the 1st quarter 2000 and the 3rd quarter of 2022.

Predicting Stock Markets Using Binary Logistic Regression Based on Bry-Boschan Algorithm

In the stock market, there are bullish and bearish terms that are reflected in the movement of the stock price index. One of the stock price indexes listed on the Indonesia Stock Exchange (IDX) is the IDX Composite. Stock market conditions fluctuate along with changes in stock prices that move randomly, while investors expect market conditions to be active (bullish market). Several factors influence the movement of the IDX Composite, one of which is macroeconomic factors. The purpose of this research is to find out the condition of stock market as well as predict its condition using macroeconomics indicators. The method used to determine stock market conditions (bullish or bearish) is the Bry-Boschan algorithm, while the method used to predict the stock market using macroeconomic indicators is the binary logistic regression method. The Bry-Boschan algorithm is widely used to detect peaks and troughs in business cycle analysis. Binary logistic regression is used to model data with responses that have two categories or are in the form of binary numbers. Results show that the IDX Composite experienced 42 times (month) bearish periods and 191 times (month) experienced bullish periods. The obtained model has an accuracy value of 81.55%.

Drivers of the Target Financial Leverage and Speed of Adjustment in Small and Medium-Sized Companies at Different Stages of Life Cycle

According to the results of recent studies, the main causes of companies’ failure are inadequate and inappropriate financing. Therefore, one of the key tasks of financial managers is to determine the best combination of the company's financial resources, or in other words, the target financial leverage. On the other hand, growth cycles are very useful for analyzing business cycles in countries that have experienced severe recessions and booms, such as Iran. The purpose of this study is to investigate the drivers of the target financial leverage and the speed of adjustment of financial leverage at different Stages of the life cycle. The statistical population is small and medium-sized companies active in Tehran Stock Exchange. For this purpose, 112 companies were selected by systematic elimination sampling method between 2015 to 2020 and views 9 software was used. The results indicate that for firms in the growth and maturing stages of their lifecycle, profitability, firm size, and tangible assets are stronger positive drivers for target leverage and when the company One stage of the life cycle goes to the next, the company slows down its gap with the target lever, and the speed of adjusting the optimal structure is reduced.

Extreme Weather Events and Economic Activity: The Case of Low Water Levels on the Rhine River

Abstract We make use of historical data on water levels on the Rhine river to analyze the impact of weather-related supply shocks on economic activity in Germany. Our analysis shows that low water levels lead to severe disruptions in inland water transportation and cause a significant and economically meaningful decrease of economic activity. In a month with 30 days of low water, industrial production in Germany declines by about 1 percent, ceteris paribus. Our analysis highlights the importance of extreme weather events for business cycle analysis and contributes to gauging the costs of extreme weather events in advanced economies.

Panel VAR for Analyzing Business Cycle Influence on the Distribution of Sharia Banking Financing in Indonesian Sharia Banking

This paper is structured to explain the effect of the business cycle on the distribution of Islamic banking financing in Indonesia. Furthermore, this research examined the differences between account receivables financing and profit-sharing financing, as well as different forms of Islamic banking. In this case, Islamic banking financing, account receivables financing, and profit-sharing financing will have the same responses or changes in the face of the business cycle in Indonesia. This research is focused and limited to the response of Islamic banking financing to the business cycle in Indonesia. Second, this research used quarterly data from 2007 to 2020 obtained from financial data of each sharia commercial bank and sharia business unit published through the Financial Services Authority (OJK) and Bank of Indonesia; meanwhile, the macro-level data was taken from data from the Central Agency publication Indonesian Statistics. Third, the estimation method used is the Panel VAR to accommodate the heterogeneity between firms. The results show that capital and liquidity respond positively to changes in banking financing, account receivables financing, and profit-sharing financing. The results also show that performing loans and profitability will decrease if there is a shock to the three types of financing.

Наукастинг выпуска обрабатывающей промышленности России с использованием данных опросов предприятий

This article is devoted to checking the possibility of using business survey data surveys to nowcasting of Russian manufacturing output: analysis of business cycles and short-term forecasting (1 month ahead). The study uses data from business surveys of the Federal State Statistics Service, the Russian Union of Industrialists and Entrepreneurs and S&P Global. The results of these surveys are published promptly (20 days or more ahead of the release of official statistics) and are freely available. The study shows that the indicators of the Federal State Statistics Service (economic situation, number of employees, business confidence index, output, demand, export) allow to increase the accuracy of forecasts by 21–39 % and have a high correlation with business cycles of the manufacturing industry. In general, the use of most business survey indicators improves short-term forecasts of manufacturing output, more than half of the indicators have a correlation coefficient greater than 0,8 with the business cycles of this sector of the economy.

A Boosted Hp Filter for Business Cycle Analysis: Evidence from New Zealand's Small Open Economy.

A Boosted Hp Filter for Business Cycle Analysis: Evidence from New Zealand's Small Open Economy.

Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics

Quarterly GDP Estimates for the German States: New Data for Business Cycle Analyses and Long-Run Dynamics

Tourism and Business Cycles: Does the Relationship Fade Away?

Abstract For a long time, tourism has been considered a social, economic and environmental phenomenon that provides products and services whose consumption is supposed to surge in periods of economic growth and wane in periods of slowdown, thereby acting procyclical. To examine this hypothesis, we have explored the exact behavior of tourism activity before and after the last big economic crisis – the Great Recession 2008 followed by the European Sovereign Debt Crisis. We have applied a methodology of business cycle analysis to investigate the relationship between the cyclical components of GDP and tourism nights spent by the residents of 23 EU member states in the 1996-2018 period. We report an important structural change in the relationship between tourism and business cycles. The relationship became apparently weaker over time and finally became insignificant after the end of the crisis, suggesting a smooth structural change. Our findings suggest uncertainty as to how tourism activity would restore its usual dynamics following the end of the current COVID-19 pandemic recession.