Cyclical Components Research Articles

Recent Developments in Macro-Econometric Modeling: Theory and Applications

Developments in macro-econometrics have been evolving since the aftermath of the Second World War.[...]

USING SYMMETRIC AND ASYMMETRIC FILTERS IN EVALUATION OF UNDERWRITING CYCLES LENGTH

The paper analyses methods for evaluation of underwriting cycle’s length and their usage in the developed decision support system for formation of effective insurance company strategy. Baxter and King along with symmetric and asymmetric Cristiano and Fitzgerald band-pass filters are applied to ex- tract medium-term cyclical component in loss ratio time series of property, CTP, and property and liabil- ity insurance. Then, using second order autoregression model we get real underwriting cycle’s length.

Cyclicality in losses on bank loans

SummaryBased on unique data we show that macro variables, the default rate and loss given default of bank loans share common cyclical components. The innovation in our model is the distinction between loans with either severe or mild losses. The variation in the proportion of these two types drives the cyclic behavior of the loss given default and constitutes the links with the default rate and macro variables. These links vary according to loan and borrower characteristics. During downturns, the proportion of defaults with severe losses increases, but the distribution of losses conditional on their being mild or severe does not change. although loans are monitored more closely than bonds and are more senior, the cyclical variation in their losses resembles those for bonds, albeit around a lower average level. This variation leads to an increase in the capital reserves required for loan portfolios.

Donor Country’s Fiscal Status and ODA Decisions before and after 2008 Global Financial Crisis

Purpose - The purpose of this study is to empirically investigate the impact of donor's fiscal status on aid decisions before and after the 2008 global financial crisis. The effects on aid can change depending on the donor country's fiscal status and the period of financial crisis. Research design, data, and methodology - A fixed effect regression and dynamic panel GMM is conducted using a comprehensive dataset combining 31 donor and 167 recipient countries during 1996-2015. The key explanatory variable is central government debt-to-GDP ratio of donor country. Recipient countries' GNI per capita, population, governance indicators, and bilateral trade-to-GDP ratio between donor and recipient countries are included as control variables. Results - We can confirm the relationship between donor country's fiscal status and aid flow. The cyclical component of government debt is found to have a negative impact on grant decisions particularly after the 2008 global financial crisis. This effect becomes larger in the countries with high government debt-to-GDP ratio. ODA decisions from the countries with low financial constraint do not significantly affected by the recipient countries' factors such as GNI, population, and governance indicator. Conclusions - Based on the empirical results of this study, the source of aid should be diversified by incorporating private sector and innovative financing sources.

Several least-squares problems related to the Hodrick–Prescott filtering

ABSTRACTThe Hodrick–Prescott (HP) filtering is frequently used in macroeconometrics to decompose time series, such as real gross domestic product, into their trend and cyclical components. Because the HP filtering is a basic econometric tool, it is necessary to have a precise understanding of the nature of it. This article contributes to the literature by listing several (penalized) least-squares problems that are related to the HP filtering, three of which are newly introduced in the article, and showing their properties. We also remark on their generalization.

Stock Return Predictability: Using the Cyclical Component of the Price Ratio

This paper considers whether the cyclical component of the log dividend-price and price-earnings ratios contain forecast power for stock returns. While the levels of these series contain slow moving information for predicting long horizon returns, for short-horizon returns it is the relative movement between prices and fundamental that matters for investors, and whether prices are accelerating away or converging with fundamentals. We use three approaches to extract the cyclical component of these ratios and conduct a range of in-sample and out-of-sample tests. In addition to the cyclical components, we include further predictive variables that account for economic growth and the relation between stocks and bonds. In-sample estimation using the ratio levels reveals results that do not accord with economic intuition. In contrast, using the cyclical component leads to economically sensible values, as well as improved in-sample fit. Out of-sample forecasting reveals that in comparison to a historical mean model, the performance of our predictive models is generally better, although that depends on metrics used to evaluate the forecasts. Moreover, the cyclical component models outperform the levels based models. Notably, the historical mean model is preferred using standard mean absolute and squared errors measures but the predictive models perform better using Mincer-Zarnowitz and related encompassing regressions. Notably, when using economic based forecast evaluation, the predictive models are clearly preferred, with a stronger ability to predict the future direction of return movements and in obtaining higher trading returns. A further examination of the results reveals that this greater performance largely arises from a superior ability to predict future negative returns.

A Closed Form Multivariate Linear Filter

This paper considers the problem of jointly decomposing a set of time series variablesinto cyclical and trend components, subject to sets of stochastic linear restrictionsamong these cyclical and trend components. We derive a closed form solution to anordinary problem featuring homogeneous penalty term difference orders and staticrestrictions, as well as to a generalized problem featuring heterogeneous penalty termdifference orders and dynamic restrictions. We use our Generalized Multivariate LinearFilter to jointly estimate potential output, the natural rate of unemployment and thenatural rate of interest, conditional on selected equilibrium conditions from a calibratedNew Keynesian model.

A Closed Form Multivariate Linear Filter

This paper considers the problem of jointly decomposing a set of time series variables into cyclical and trend components, subject to sets of stochastic linear restrictions among these cyclical and trend components. We derive a closed form solution to an ordinary problem featuring homogeneous penalty term difference orders and static restrictions, as well as to a generalized problem featuring heterogeneous penalty term difference orders and dynamic restrictions. We use our Generalized Multivariate Linear Filter to jointly estimate potential output, the natural rate of unemployment and the natural rate of interest, conditional on selected equilibrium conditions from a calibrated New Keynesian model.

Rethinking Capital Regulation: The Case for Dividend Prudential Target

The paper investigates the effectiveness of dividend-based macroprudential rules in complementing capital requirements to promote bank soundness and sustained lending over the cycle. First, some evidence on bank dividends and earnings in the euro area is presented. When shocks hit their profits, banks adjust retained earnings to smooth dividends. This generates bank equity and credit supply volatility. Then, a DSGE model with key financial frictions and a banking sector is developed to assess the virtues of what shall be called dividend prudential targets. Welfare-maximizing dividend-based macroprudential rules are shown to have important properties: (i) they are effective in smoothing the financial and the business cycle by means of less volatile bank retained earnings, (ii) they induce welfare gains associated to a Basel III-type of capital regulation, (iii) they mainly operate through their cyclical component, ensuring that long-run dividend payouts remain unaffected, (iv) they are flexible enough so as to allow bank managers to optimally deviate from the target (conditional on the payment of a sanction), and (v) they are associated to a sanctions regime that acts as an insurance scheme for the real economy.

Multivariate Bayesian structural time series model

This paper deals with inference and prediction for multiple correlated time series, where one also has the choice of using a candidate pool of contemporaneous predictors for each target series. Starting with a structural model for time series, we use Bayesian tools for model fitting, prediction and feature selection, thus extending some recent works along these lines for the univariate case. The Bayesian paradigm in this multivariate setting helps the model avoid overfitting, as well as captures correlations among multiple target time series with various state components. The model provides needed flexibility in selecting a different set of components and available predictors for each target series. The cyclical component in the model can handle large variations in the short term, which may be caused by external shocks. Extensive simulations were run to investigate properties such as estimation accuracy and performance in forecasting. This was followed by an empirical study with one-step-ahead prediction on the max log return of a portfolio of stocks that involve four leading financial institutions. Both the simulation studies and the extensive empirical study confirm that this multivariate model outperforms three other benchmark models, viz. a model that treats each target series as independent, the autoregressive integrated moving average model with regression (ARIMAX), and the multivariate ARIMAX (MARIMAX) model.

Nonlinear Differential Equation of Macroeconomic Dynamics for Long-Term Forecasting of Economic Development

In this article we derive a general differential equation that describes long-term economic growth in terms of cyclical and trend components. Equation is based on the model of non-linear accelerator of induced investment. A scheme is proposed for obtaining approximate solutions of nonlinear differential equation by splitting solution into the rapidly oscillating business cycles and slowly varying trend using Krylov-Bogoliubov-Mitropolsky averaging. Simplest modes of the economic system are described. Characteristics of the bifurcation point are found and bifurcation phenomenon is interpreted as loss of stability making the economic system available to structural change and accepting innovations. System being in a nonequilibrium state has a dynamics with self-sustained undamped oscillations. The model is verified with economic development of the US during the fifth Kondratieff cycle (1982-2010). Model adequately describes real process of economic growth in both quantitative and qualitative aspects. It is one of major results that the model gives a rough estimation of critical points of system stability loss and falling into a crisis recession. The model is used to forecast the macroeconomic dynamics of the US during the sixth Kondratieff cycle (2018-2050). For this forecast we use fixed production capital functional dependence on a long-term Kondratieff cycle and medium-term Juglar and Kuznets cycles. More accurate estimations of the time of crisis and recession are based on the model of accelerating log-periodic oscillations. The explosive growth of the prices of highly liquid commodities such as gold and oil is taken as real predictors of the global financial crisis. The second wave of crisis is expected to come in June 2011.

Different Versions of the Easterlin Paradox: New Evidence for European Countries

Richer people are happier than poorer people, but when a country becomes richer over time, its people do not become happier. This seemingly contradictory pair of findings of Richard Easterlin has be-come famous as the Easterlin Paradox. However, it was met with counterevidence. To shed more light on this controversy, we distinguish between five different versions of the paradox. These versions apply to either groups of countries or individual countries, and to either the long or the medium term. We argue that the long term is most appropriate for testing the paradox, and that tests of the paradox should always control for an autonomous time trend. Unfortunately, this requirement renders the long-term version of the paradox for individual countries untestable. We test all other versions of the paradox with Eurobarometer data from 27 European countries. We do so by estimating country-panel equations for mean life satisfaction that include trend and cyclical components of per capita GDP as regressors. When testing variants of the paradox that apply to groups of countries, we find a clear and robust confirmation of the long- and medium-term versions of the paradox for a group of nine Western and Northern European countries. Moreover, we obtain a non-robust rejection of the medium-term variant of the paradox for a set of eleven Eastern European countries. On the level of individual countries, the medium-term variant of the paradox clearly holds for the nine Western and Northern European countries, but is consistently rejected for Greece, Ireland, Italy, and Spain. In the case of the Eastern European countries, the medium-term version of the paradox is rejected for Bulgaria, Lithuania, and Poland. As the Western and Northern European countries have a high per capita GDP as compared to that of Southern and Eastern European countries, our results are in line with the finding of Proto and Rustichini (2013), who find a non-monotonic relation between per capita GDP and life satisfaction over time which is positive for poorer countries, but flat (or negative) for richer countries.

Cyclical Earnings and Stock Index Crash Risk

Stock market fundamentals would not seem to meaningfully predict returns over a shorter-term horizon --- yet some economic agents could be particularly concerned about severe tail risk, rather than just mean returns. Motivated by present value logic, and the literature's suggestion that required equity returns have declined over time, I first estimate the cointegrating relationship between the log S&P Composite Index and log earnings over 1871 to 2016. I combine this estimate with smoothed earnings to construct a trend valuation benchmark. The price-versus-benchmark residual reflects, in part, the cyclical component of earnings, and gives an economically and statistically significant estimate of crash risk while improving on alternatives such as the dividend yield and price momentum.

Persistence and Cyclical Dynamics of U.S. and U.K. House Prices: Evidence from Over 150 Years of Data

This paper provides a new and unique look at the dynamics and persistence of historical house prices in the US and the UK using fractional integration techniques not previously applied to housing markets. We use annual data from 1830 to 2016 for the US and 1845 to 2016 for the UK, which provides a much longer perspective on the behavior of house prices than is common in the literature, where most empirical work uses data starting from the 1980s or later. Unlike previous research, we consider two components of persistence of house prices: the component associated with the long-run trend (i.e. at frequency zero) and the component associated with the cycle (i.e. at frequency away from zero). We find convincing evidence that in the UK, housing markets incorporate two distinct poles in house price dynamics, at the zero (long-run trend) and non-zero (cyclical) frequencies. In contrast, we fail to find evidence of cyclical persistence for the US. For the sub-samples, which account for a structural break in each series, an important difference is the asynchronous pattern of the breaks, an indication of heterogeneity in the house price dynamics of the two countries and a sign that national rather than global events have played an important role. Although the house price movements of the last decade are dramatic, the greatest structural changes in the overall nominal and real price dynamics of the UK and the US appear to have taken place much earlier, in the late 1970s and early 1980s in the UK, and in the mid-1950s and early 1970s in the US. An important result, common to the whole and sub-samples, is that long-run persistence plays a greater role than cyclical persistence in explaining the dynamics of house prices in both countries. These findings have substantial implications for policy decisions. Shocks affecting the long-run component will persist for a long time, while those affecting the cyclical component will not. Thus, policymakers should adopt stronger policies with respect to long-run house price movements to create an environment whereby housing markets can readily revert to their original trends.

A Statistical Analysis of Cyclical Changes in the Time Series of Meteorological Parameters in the Southwest of the Valdai Hills

A statistical analysis of periodic and cyclical components of time series of meteorological parameters was conducted for the 40-year observation period in the southwest of the Valdai Hills by classic seasonal decomposition and Fourier analysis. The dependence of the obtained OLS estimates of linear-regression models of meteorological parameters on a length of the smoothing interval was analyzed. Cyclical fluctuations in the time series of temperature with periods of 8 and 3 years and those of rainfall with periods of 3.5 and 10.5 years were detected and analyzed.

Business Cycles and Start-Ups Across Industries: An Empirical Analysis of German Regions

We analyze whether start-up rates in different industries systematically change with business cycle variables. Using a unique data set at the industry level, we mostly find correlations that are consistent with counter-cyclical influences of the business cycle on entries in both innovative and non-innovative industries. Entries into the large-scale industries, including the innovative part of manufacturing, are only influenced by changes in the cyclical component of unemployment, while entries into small-scale industries, like knowledge intensive services, are mostly influenced by changes in the cyclical component of GDP. Thus, our analysis suggests that favorable conditions in terms of high GDP might not be germane for start-ups. Given that both innovative and non-innovative businesses react counter-cyclically in 'regular' recessions, business formation may have a stabilizing effect on the economy.

A flexible nonlinear inference to Okun’s law for Turkish economy in the last decade

The study applies the flexible nonlinear inference approach of James D. Hamilton (2001) to investigate the relationship between cyclical components of unemployment and output in the Turkish economy where the unemployment rate remains at double digits despite the relatively stable economic environment over the last decade. The paper shows that economic expansion and contraction terms have an asymmetric effect on cyclical unemployment in Turkey. Moreover, the study identifies a specific range for the output gap level at which jobless growth pattern occurs in the Turkish economy. According to our findings, contrary to standard literature, cyclical component of unemployment does not decrease even though cyclical component of output is positive and increases in the middle stages of the upswing phase of the economy. This result may also indicate that the employers are reluctant to extend employment and alter into informalization for reasons such as over-valued domestic currency, surplus labour force and/or any rigid regulatory frameworks in the middle stages of the expansion phase of the economy. However, they become eager to expand employment and renounce informalization only after a certain rate of economic growth is achieved.

Econometric Convergence Test and Club Clustering Using Stata

In this article, I introduce a new package with five commands to perform econometric convergence analysis and club clustering as proposed by Phillips and Sul (2007, Econometrica 75: 1771–1855). The logtreg command performs the log t regression test. The psecta command implements the clustering algorithm to identify convergence clubs. The scheckmerge command conducts the log t regression test for all pairs of adjacent clubs. The imergeclub command tries to iteratively merge adjacent clubs. The pfilter command extracts the trend and cyclical components of a time series of each individual in panel data. I provide an example from Phillips and Sul (2009, Journal of Applied Econometrics 24: 1153–1185) to illustrate the use of these commands. Additionally, I use Monte Carlo simulations to exemplify the effectiveness of the clustering algorithm.

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development.

Environmental exposures to essential and toxic elements may alter health trajectories, depending on the timing, intensity, and mixture of exposures. In epidemiologic studies, these factors are typically analyzed as a function of elemental concentrations in biological matrices measured at one or more points in time. Such an approach, however, fails to account for the temporal cyclicity in the metabolism of environmental chemicals, which if perturbed may lead to adverse health outcomes. Here, we conceptualize and apply a non-linear method–recurrence quantification analysis (RQA)–to quantify cyclical components of prenatal and early postnatal exposure profiles for elements essential to normal development, including Zn, Mn, Mg, and Ca, and elements associated with deleterious health effects or narrow tolerance ranges, including Pb, As, and Cr. We found robust evidence of cyclical patterns in the metabolic profiles of nutrient elements, which we validated against randomized twin-surrogate time-series, and further found that nutrient dynamical properties differ from those of Cr, As, and Pb. Furthermore, we extended this approach to provide a novel method of quantifying dynamic interactions between two environmental exposures. To achieve this, we used cross-recurrence quantification analysis (CRQA), and found that elemental nutrient-nutrient interactions differed from those involving toxicants. These rhythmic regulatory interactions, which we characterize in two geographically distinct cohorts, have not previously been uncovered using traditional regression-based approaches, and may provide a critical unit of analysis for environmental and dietary exposures in epidemiological studies.

Application of filters to analysis of business cycles and business cycle synchronization of Poland with European countries

The aim of this paper is to present the importance of business cycle synchronization between Poland and other European countries. The Hodrick- Prescott and Christiano-Fitzgerald filters were used in the research. They were applied to extract cyclical components from quarterly time series of real GDP of 33 European countries basing on the Eurostat’s quarterly data on nominal GDP and price level in the years 2002—2016. The application of filters proved that, in case of some countries (e.g. Greece), the economic crisis led not only to a drop of GDP but also to a break in the trend. Moreover, the results indicate that most European countries overcame the crisis at the end of 2015. The business cycle synchronization of Poland with euro area countries is slowly increasing.