Business Cycle Analysis Research Articles

BEYOND RANDOM CAUSES: HARMONIC ANALYSIS OF BUSINESS CYCLES AT THE MOSCOW CONJUNCTURE INSTITUTE

This article proposes a historical assessment of harmonic analysis of business cycles and its ability to both decompose and build cycles, as received at the Moscow Conjuncture Institute. It traces how the Fourier transform arrived at the Institute, mediated by Henry L. Moore, in the works and actions of Albert Vainshtein, Nikolai Chetverikov, and Nikolai Kondratiev, ultimately leading to Eugen Slutsky’s well-known 1927 article “The Summation of Random Causes as the Source of Cyclic Processes.” Although the evidence does not warrant the assumption that there was an orchestrated effort at the Institute to push forward a research agenda on harmonic analysis of business cycles, it certainly unfolded as more than the summation of random events and individual incursions. Moreover, the Institute as a whole could have produced much more on this matter if it had escaped Stalinist oppression for at least a few more years.

Business cycle dynamics when neutral and investment-specific technology shocks are imperfectly observable

We develop a general equilibrium business cycle model with imperfectly observed neutral and investment-specific technology shocks, which agents learn from noisy signals. Estimated using US data, the model implies that neutral technology shocks generate more volatile responses than in an environment with perfect information, whereas investment-specific shocks have more persistent impact. Noise accounts for substantial variation in investment, and alters agents’ behavior persistently through its influence on beliefs — even when the underlying fundamentals are unchanged and the noise itself is not persistent. Further implications for business cycle analysis are explored.

Tax evasion and financial accelerator: A corporate sector analysis for the US business cycle

This paper investigates the consequences of willful tax noncompliance in the US corporate sector on the business cycle when financial frictions operate. In this setting, we simulate a risk shock that propagates its effects in the credit channel via a financial accelerator mechanism. In addition to emphasizing the role of tax evasion as a self-financing mechanism, the paper provides a twofold result, producing nonnegligible consequences for business cycle analysis. First, conditioned on risk shock, tax evasion strengthens the effects of the financial accelerator and amplifies macroeconomic fluctuations considerably. Second, endogenous tax evasion dynamics generates a reallocation of resources from productive to consumption uses over the business cycle.

Sentiment Dictionary for Business Cycle Analysis and its Applications

Sentiment Dictionary for Business Cycle Analysis and its Applications

Obtaining consistent time series from Google Trends

AbstractGoogle Trends data are a popular data source for research, but raw data are frequency‐inconsistent: daily data fail to capture long‐run trends. This issue has gone unnoticed in the literature. In addition, sampling noise can be substantial. We develop a procedure (available in an R‐package), which solves both issues at once. We apply this procedure to construct long‐run, frequency‐consistent daily economic indices for three German‐speaking countries. The resulting indices are significantly correlated with traditional leading economic indicators while being available in real time. We discuss potential applications across disciplines and spanning well beyond business cycle analysis.

Business Cycles Analysis in Cameroon an overview

This paper aims at conducting a thorough analysis of business cycles in Cameroon by statistically assessing their main characteristics. The analysis is carried out by considering the three dimensions of macroeconomic fluctuations. By assessing output volatility, light on the sensitivity of the economy to exogenous shocks as well as to endogenous sources of instability is shed. Likewise, analysing the co-movements of aggregate variables of interest helps in understanding the extent to which the observed fluctuations relate to other aggregates in the economy and hence, the main forces driving the dynamics of this economy. Eventually, more light could be shed on macroeconomic dynamics by analysing the timing and persistence of business cycles. Overall, such analysis is conducted using basic statistical tools commonly used in the empirical literature on business cycles. These are the standard deviation as a measure of volatility, cross-correlations as a means of analysing co-movements and auto-correlations as measures of persistence. The main limitation in this study is the linear consideration of observed data. In fact, many macroeconomic and financial time-series that are used in quantitative macroeconomic models are subject to a number of regime-switching in reality. This fact needs to be taken into account in the subsequent research

Does the Real Business Cycle Help Forecast the Financial Cycle?

This study investigates the relationship between the financial market and the real business cycle in the US from February 1987 to March 2016. Using different monthly time-series as proxies for the financial and macroeconomic cycles, we first specify the determinants and then build two indicators to measure the financial and real business cycles based on principal component analysis. We identify not only the main different cycles for each indicator but also measure the duration of the phases for each indicator. Second, we study the relationship between economic and financial indicators per cycle and per phase using a vector autoregressive model. Our findings show that the economic indicator is useful to forecast the financial, and that there exists a significant relationship between the financial and economic cycles that is actively stronger during the “expansion–growth” phase. This result enables investors and policymakers to better forecast the future dynamics of financial sector using the information provided by the analysis of the real business cycle.

Research on electric power development and economic growth in Hebei Province based on business cycle analysis

With the improvement of China’s electrification level, the relationship between electricity power consumption and social economy development is getting closer. Under this background, in this paper, the business cycle analysis method is applied to the electricity power industry in Hebei Province, and the link between electric power generation and economic development is determined through the prosperity index. First of all, the steps and methods of business cycle analysis were introduced, and the time-difference grey correlation method considering the consistency of time series to screen indicators was put forward, thus to reduce the number of indicators. Next, Hebei Province was taken as an example, and its monthly data related to power generation and economic growth in the 10 years from 2009 to 2018 to was selected to build the business cycle indicator system, at last the composite prosperity index of Hebei Province in electric power industry was calculated. This research results manifest that it is feasible to apply the business cycle analysis to the power industry.

Business Cycles Analysis in Cameroon: An Overview

This paper aims at conducting a thorough analysis of business cycles in Cameroon by statistically assessing their main characteristics. The analysis is carried out by considering the three dimensions of macroeconomic fluctuations. By assessing output volatility, light on the sensitivity of the economy to exogenous shocks as well as to endogenous sources of instability is shed. Likewise, analysing the co-movements of aggregate variables of interest helps in understanding the extent to which the observed fluctuations relate to other aggregates in the economy and hence, the main forces driving the dynamics of this economy. Eventually, more light could be shed on macroeconomic dynamics by analysing the timing and persistence of business cycles. Overall, such analysis is conducted using basic statistical tools commonly used in the empirical literature on business cycles. These are the standard deviation as a measure of volatility, cross-correlations as a means of analysing comovements and auto-correlations as measures of persistence. The main limitation in this study is the linear consideration of observed data. In fact, many macroeconomic and financial time-series that are used in quantitative macroeconomic models are subject to a number of regime-switching in reality. This fact needs to be taken into account in the subsequent research.

The Eurostat business cycle clock: A complete overview of the tool

Fluctuations of the economy between periods of expansion and contraction have been subject to business cycle analysis for many years. However, the understanding of different cycles, such as business, growth and acceleration cycles, and their representation in an intuitive way is not straightforward. Moreover, users are confronted with large sets of economic indicators without having synthetic information on the current evolution of the economy. In this paper, we introduce the Eurostat business cycle clock (BCC), a visualization tool designed to complement traditional economic statistics. We will present the full methodological framework underlying the clock, including the statistical detection of turning points, empirical dating and assessment. The clock is available for the euro area and its member countries, although our presentation will focus on the euro area aggregate. Some brief considerations on the impact of the current COVID-19 crisis on the clock are included.

Green business cycle: an analysis on China and France

Business cycle analysis generated an essential impulse in stimulating and provoking interesting academic and professional debates within a growth perspective. In fact, measuring business cycles is critical in determining the stylized facts on the cyclical behavior of aggregate macroeconomic indicators over time. As green growth topics started to occupy much academic interest, the question of the co-existence of equitable and sustainable development as well as current dynamics and cyclical features of economic growth comes into foreplay. This paper aims to evaluate cyclical characteristics of green growth related variables by observing two countries that showed different green policy aspirations over time, namely China and France. Following the paper's main objective, we want to provide a detailed analysis of the extent to which Green GDP and relevant output measures are comparable in a wider 'deviation cycle' context that includes cycle correlation, cycle coherence, and cycle magnitude. Results suggest that business cycles of GDP/GNI and Green GDP are strongly connected and coherent to a high degree. However, we found that the strength of that nexus and the degree of similarity has changed considerably over time, yet in a positive way.

Credit decomposition and economic activity in Turkey: A wavelet-based approach

This paper aims to investigate the co-movement between the credit growth and gross domestic product (GDP) growth in Turkey over the period January 2004–October 2019. By taking into account alternative credit decomposition and the variations over time and across frequencies using the wavelet analysis, the results show that: i) GDP growth highly synchronizes with credit growth compared to other financial variables such as stock exchange, bonds, and exchange rate. ii) There is a high correlation between commercial loan growth and capital formation and a relatively weak one with consumer loans and consumption. iii) Co-movement stemming from Turkish Lira (TL) credits to GDP growth is stronger than foreign exchange (FX) credits where the latter is significant until 2015. iv) Public and domestic private banks are the main drivers of economic activity while the foreign banks are following them. By showing the differential effects of different types of credit on GDP growth, we specify that shocks to different credit types are crucial to analyze business cycles. For policymakers, this result implies that the dynamics of different credit types are crucial to analyze the impacts of credit cycles on economic activity.

Monetary policy and consumers' demand

This paper puts to scrutiny the way monetary policy propagates its effects and the way it should be conducted, focusing on the behavior of consumers. Specifically, it considers a price elasticity of demand that increases with the level of consumption as is observed in the data. A realistic demand structure has remarkable implications for monetary policy. Three main results stand out. First, it can amplify the real effects of monetary and technology shocks. Second, it can weaken the ability of a simple Taylor rule to stabilize the economy. Third, it can attenuate the trade-off in the stabilization of output and inflation. These findings provide support to the notion of a dual mandate for the central bank. They are based on a novel mechanism of intertemporal substitution, whereby consumers have a weak incentive to smooth out the effects of income fluctuations. The mechanism lends itself to addressing questions of stabilization policy and business cycle analysis.

Walter Eucken’s Concept of Economic Order and Business Cycle Analysis

AbstractWalter Eucken formulated his concept of economic order as a solution to the tension between theoretical approaches and empirical observation that had constituted the conflict between the Austrian School of Economics and the German Historical School. Previous literature has established the linkage between the German-language business cycle debate of the late 1920 s and Eucken’s concept of economic order. This paper discusses how his concept of economic order can help to understand the severity of economic crises and thus concentrates on the elements constituting the economic order, i. e. its ideal types, with whose help Eucken aimed to derive hypothetical propositions. Based on the writings of his students Leonhard Miksch and Friedrich A. Lutz who underscored the role of equilibrium in business cycle research, this paper suggests that abstract theory of economic crises should employ ideal types as models and thus study how exogenous shocks affect the endogenous economic variables. The subject of inquiry should be oriented to the process of equilibrium reestablishment. Crucial for this paper is that the equilibrium reestablishment depends on institutional factors. This method to explain economic crises represents the link which connects the business cycle debate of the 1920 s and 1930 s to the subsequent emergence of the ordoliberal theory of institutions and orders.

Sectoral shifts and comovements in employment

Sectoral shifts in employment from manufacturing to services are viewed as a structural transformation which occurs over a long period of time. Economists point out that a rapid technological advance in the manufacturing sector relative to that in the service sector is the underlying cause of this phenomenon. However, few have associated this with business cycle analyses. This paper finds that a relatively faster technological advance in the manufacturing sector (named manufacturing-specific technology shock) generates sectoral comovements in employment in the short run while it leads to sectoral shifts in employment in the long run. The behavior of investment is the key to this finding.

Cross-sectional and aggregate labor supply

Standard heterogeneous agent macro models that highlight idiosyncratic productivity shocks do not generate the near zero cross-sectional correlation between hours and wages found in the data. We ask whether matching this moment matters for business cycle properties of these models. To do this we explore two extensions of the model in Chang et al. (2019) that can match this empirical cross-section correlation. One of these departs from the assumption of balanced growth preferences. The other introduces an idiosyncratic shock to the opportunity cost of market work that is highly correlated with the shock to market productivity. While both extensions can match the empirical correlation, they have large and opposing effects on the cyclical volatility of the labor market. We conclude that the cross-sectional moment is important for business cycle analysis and that more work is needed to distinguish the potential mechanisms that can generate it.

A Markov‐switching analysis of Nigeria's business cycles: Are election cycles important?

AbstractThe study examines Nigeria's business cycles between October 1998 and October 2017 and ascertains the importance of general elections cycles in engendering cyclical fluctuations in different measures of business cycles.A framework based on political business cycles theory was estimated with a dynamic Markov‐switching regression technique. The study finds that election cycles are adequate in predicting cycles in food prices, non‐farm prices, exports, and imports in Nigeria while a significant effect of election cycles on the stock market, general price level, and exchange rate could not be established. The study concludes that cycles in food, non‐farm prices, imports, and exports can be predicted by future general elections while re‐election seeking behaviour of politicians lacks the power to influence stock market performance and exchange rate in Nigeria. Hence, artificial business cycles that result primarily from politicians manipulating certain fiscal tools targeted at stimulating the economy only to increase the re‐election chances could be minimized if monetary and fiscal institutions are strong, effective, and truly independent. This will ensure that policies are not manipulated between elections by politicians but are well targeted at achieving a set of long‐term developmental goals.

A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis.

This paper develops a dynamic factor model that uses euro area country‐specific information on output and inflation to estimate an area‐wide measure of the output gap. Our model assumes that output and inflation can be decomposed into country‐specific stochastic trends and a common cyclical component. Comovement in the trends is introduced by imposing a factor structure on the shocks to the latent states. We moreover introduce flexible stochastic volatility specifications to control for heteroscedasticity in the measurement errors and innovations to the latent states. Carefully specified shrinkage priors allow for pushing the model towards a homoscedastic specification, if supported by the data. Our measure of the output gap closely tracks other commonly adopted measures, with small differences in magnitudes and timing. To assess whether the model‐based output gap helps in forecasting inflation, we perform an out‐of‐sample forecasting exercise. The findings indicate that our approach yields superior inflation forecasts, both in terms of point and density predictions.

Welfare Consequences of Approximation Methods in a Nonlinear Model

This paper investigates the welfare consequences of approximation methods conventionally used in business cycle analysis: the log-linear approximation of model dynamics and the second-order approximation of social welfare. In a canonical sticky-price business cycle model, the approximation around the deterministic steady state substantially understates the welfare losses associated with price rigidities as it fails to capture the misallocations in a steady state induced by precautionary behavior. Instead, the approximation around the risky steady state, which takes the precautionary behavior into account, delivers much smaller approximation errors. Implications to the optimal monetary policy and those in extended models are explored.

Putting the Cycle Back into Business Cycle Analysis

Are business cycles mainly a response to persistent exogenous shocks, or do they instead reflect a strong endogenous mechanism which produces recurrent boom-bust phenomena? In this paper we present evidence in favor of the second interpretation and we highlight the set of key elements that influence our answer. The elements that tend to favor this type of interpretation of business cycles are (i) slightly extending the frequency window one associates with business cycle phenomena, (ii) allowing for strategic complementarities across agents that arise due to financial frictions, and (iii) allowing for a locally unstable steady state in estimation. (JEL E22, E24, E23, E44)