Endogenous Cycles Research Articles

Two Complementary Signaling Pathways Depict Eukaryotic Chemotaxis: A Mechanochemical Coupling Model.

Many eukaryotic cells, including neutrophils and Dictyostelium cells, are able to undergo correlated random migration in the absence of directional cues while reacting to shallow gradients of chemoattractants with exquisite precision. Although progress has been made with regard to molecular identities, it remains elusive how molecular mechanics are integrated with cell mechanics to initiate and manipulate cell motility. Here, we propose a two dimensional (2D) cell migration model wherein a multilayered dynamic seesaw mechanism is accompanied by a mechanical strain-based inhibition mechanism. In biology, these two mechanisms can be mapped onto the biochemical feedback between phosphoinositides (PIs) and Rho GTPase and the mechanical interplay between filamin A (FLNa) and FilGAP. Cell migration and the accompanying morphological changes are demonstrated in numerical simulations using a particle-spring model, and the diffusion in the cell membrane are simulations using a one dimensional (1D) finite differences method (FDM). The fine balance established between endogenous signaling and a mechanically governed inactivation scheme ensures the endogenous cycle of self-organizing pseudopods, accounting for the correlated random migration. Furthermore, this model cell manifests directional and adaptable responses to shallow graded signaling, depending on the overwhelming effect of the graded stimuli guidance on strain-based inhibition. Finally, the model cell becomes trapped within an obstacle-ridden spatial region, manifesting a shuttle run for local explorations and can chemotactically “escape”, illustrating again the balance required in the complementary signaling pathways.

P–681 Will the hCG trigger dose used for final oocyte maturation in IVF impact endogenous progesterone during the luteal phase? - A randomized controlled trial

Abstract Study question Is there an association between the hCG dose used for ovulation trigger and the endogenous progesterone production during the luteal phase? Summary answer Increased hCG dosing significantly increased the endogenous progesterone level during the luteal phase. What is known already During the luteal phase of an IVF treatment, the endogenous progesterone (P4) production is negatively impacted due to reduced circulating endogenous LH, caused by negative feed-back of elevated steroids; thus, luteal phase support (LPS) with exogenous P4 remains mandatory in IVF. Apart from inducing final oocyte maturation, the gold standard HCG trigger also functions as an early LPS, boosting P4 production by the corpora lutea (CL). P4 plays a pivotal role for embryo implantation and pregnancy, and an optimal P4 level around peri-implantation seems to be essential for the reproductive outcomes of fresh and frozen/thaw embryo transfer cycles. Study design, size, duration A randomized controlled 4-arm study, including a total of 127 IVF patients, enrolled from January 2015 until September 2019 at the Fertility Clinic, Odense University Hospital, Denmark. Participants/materials, setting, methods IVF patients with ≤ 11 follicles ≥ 12 mm were randomized to four groups. Groups 1–3 were triggered with: 5.000 IU, 6.500 IU or 10.000 IU, hCG, respectively, receiving a LPS consisting of 17-α-hydroxy-progesterone (17α OH P4) to distinguish the endogenous P4 from the exogenous supplementation. Group 4 (control) was randomized to a 6.500 IU hCG trigger and standard LPS. A total of eight blood samples were drawn during the early luteal phase. Main results and the role of chance A total of 94 patients completed the study: 21, 22, 25 and 26 patients in each group, respectively. Baseline characteristics were similar, except for the endogenous LH level and cycle lengths. There were no significant differences between groups regarding ovarian stimulation, number of oocytes and embryos. The median number of follicles ≥ 12mm on the day of trigger was 8.5, resulting in 6.6 oocytes being retrieved. Significant differences in P4 levels were seen at OPU+8 (p < 0.001), OPU+10 (p < 0.001) and OPU+14 (p < 0.001), with positive correlations between P4 level and hCG dose. Groups compared individually showed significant difference in P4 between low and high trigger dose at OPU+4 group 1 and 3 (p = 0.037) and OPU+8 group 1 and 3 (p = 0.007) and between all the three groups around implantation at OPU+6 group 1 and 2 (p = 0.011), group 2 and 3 (p = 0.042) and group 1 and 3 (p < 0.001). Higher P4 levels around implantation were related to follicle count and to pregnancy. After logistic regression analyses there were still significant individual differences between the groups. Limitations, reasons for caution Although patients were randomized and strict inclusion and exclusion criteria were used, the RCT was un-blinded, including a relatively small number of patients. Moreover, for dosing purposes urinary hCG as well as recombinant hCG was used and pharmacokinetics differ. Finally, the P4 level could be influenced by circadian fluctuations. Wider implications of the findings: This is the first study to explore dose-responses in circulating P4 after hCG trigger in IVF patients. Increasing the hCG trigger dose increased the endogenous P4 around peri-implantation. Personalizing the hCG trigger dose could be a key point to secure the most optimal P4 mid-luteal phase P4 level. Trial registration number Eudract 2013–003304–39

P-681 Will the hCG trigger dose used for final oocyte maturation in IVF impact endogenous progesterone during the luteal phase? - A randomized controlled trial

Abstract Study question Is there an association between the hCG dose used for ovulation trigger and the endogenous progesterone production during the luteal phase? Summary answer Increased hCG dosing significantly increased the endogenous progesterone level during the luteal phase. What is known already During the luteal phase of an IVF treatment, the endogenous progesterone (P4) production is negatively impacted due to reduced circulating endogenous LH, caused by negative feed-back of elevated steroids; thus, luteal phase support (LPS) with exogenous P4 remains mandatory in IVF. Apart from inducing final oocyte maturation, the gold standard HCG trigger also functions as an early LPS, boosting P4 production by the corpora lutea (CL). P4 plays a pivotal role for embryo implantation and pregnancy, and an optimal P4 level around peri-implantation seems to be essential for the reproductive outcomes of fresh and frozen/thaw embryo transfer cycles. Study design, size, duration A randomized controlled 4-arm study, including a total of 127 IVF patients, enrolled from January 2015 until September 2019 at the Fertility Clinic, Odense University Hospital, Denmark. Participants/materials, setting, methods IVF patients with ≤ 11 follicles ≥ 12 mm were randomized to four groups. Groups 1-3 were triggered with: 5.000 IU, 6.500 IU or 10.000 IU, hCG, respectively, receiving a LPS consisting of 17-α-hydroxy-progesterone (17α OH P4) to distinguish the endogenous P4 from the exogenous supplementation. Group 4 (control) was randomized to a 6.500 IU hCG trigger and standard LPS. A total of eight blood samples were drawn during the early luteal phase. Main results and the role of chance A total of 94 patients completed the study: 21, 22, 25 and 26 patients in each group, respectively. Baseline characteristics were similar, except for the endogenous LH level and cycle lengths. There were no significant differences between groups regarding ovarian stimulation, number of oocytes and embryos. The median number of follicles ≥ 12mm on the day of trigger was 8.5, resulting in 6.6 oocytes being retrieved. Significant differences in P4 levels were seen at OPU+8 (p < 0.001), OPU+10 (p < 0.001) and OPU+14 (p < 0.001), with positive correlations between P4 level and hCG dose. Groups compared individually showed significant difference in P4 between low and high trigger dose at OPU+4 group 1 and 3 (p = 0.037) and OPU+8 group 1 and 3 (p = 0.007) and between all the three groups around implantation at OPU+6 group 1 and 2 (p = 0.011), group 2 and 3 (p = 0.042) and group 1 and 3 (p < 0.001). Higher P4 levels around implantation were related to follicle count and to pregnancy. After logistic regression analyses there were still significant individual differences between the groups. Limitations, reasons for caution Although patients were randomized and strict inclusion and exclusion criteria were used, the RCT was un-blinded, including a relatively small number of patients. Moreover, for dosing purposes urinary hCG as well as recombinant hCG was used and pharmacokinetics differ. Finally, the P4 level could be influenced by circadian fluctuations. Wider implications of the findings This is the first study to explore dose-responses in circulating P4 after hCG trigger in IVF patients. Increasing the hCG trigger dose increased the endogenous P4 around peri-implantation. Personalizing the hCG trigger dose could be a key point to secure the most optimal P4 mid-luteal phase P4 level. Trial registration number Eudract 2013-003304-39

Failing outward: power politics, regime complexity, and failing forward under deadlock

ABSTRACT Failing forward describes an endogenous cycle of EU institution-building through lowest-common denominator breakthroughs in Council. This article adds a dynamic called failing outward, in which a powerful country steers EU law and policy from outside the EU. Where strong Council deadlocks persist during crises, and a powerful state possesses a critical, excludable resource, it will make access conditional on EU rules and institutions that reflect its own interests rather than Council compromises. A non-EU institution helps it do this, entrenching conditionality. Repeated institutional fixes follow as the system fails (some) other Member States. This model is applied to Germany’s effective authority through the European Stability Mechanism over Council and Commission in determining EMU reforms, including Banking Union.

Nonlinear models of the Phillips curve

The recent flattening of the Phillips curve has stimulated new empirical research and theoretical discussions regarding the nonlinear nature of the changes in the parameters. The objective of the present paper is twofold: to detect the relevant type of the implied nonlinearity and look for some general model capable of generating a Phillips curve mimicking the empirical one. We find evidence of a convex US price Phillips curve, from 1961 q1 to 2019 q4, assessed both by piecewise and threshold models. The result presents some degree of novelty regarding the role of supply shocks and model-specific convexities; in addition, it supports the use of a regime-switching macro system. The latter accomplishes three tasks. It can generate a Phillips curve resembling its empirical counterparts; it creates a medium-run endogenous cycle where unemployment is not a NAIRU; finally, it opens new perspectives on economic policy issues.

Leverage cycles when banks have a choice

Leveraged investing can aggravate crises when dropping asset prices force sales in falling markets. Leverage control policies introduced to coun- teract this could lead to agents targeting the maximal leverage deemed ‘prudent’ at all times. Aymanns and Farmer (2015) show how, for a Value at Risk type control policy, this ‘leverage targeting’ can not only lead to aggravated crises, but can also trigger the crisis to begin with and cause the boom that follows it. In modelling a whole cycle, however, the assumptions that investors base their demand for risky assets only on their leverage target becomes more dubious. In this paper, we allow our agents to repeatedly choose between a leverage targeting and a (leverage constrained) expected utility optimisation strategy. We find that both strategies persist, and in fact are equally prevalent on average. The endogenous cycles that Aymanns and Farmer (2015) found persist, although their amplitude is reduced. Agents will thus regularly choose to invest up to their leverage constraint, without further consideration of the state of the market, even though this destabilises the market. We find that allowing short-selling for agents using the optimisation strategy does stabilise the market.

Existence and implications of a pitchfork-Hopf bifurcation in a continuous-time two-sector growth model

This paper shows that the dynamics of the Lucas (J Monet Econ, 22:3–42, 1988) endogenous growth model with flow externalities may give rise to a 2-torus, a compact three-dimensional manifold enclosed by a two-dimensional surface. The implications of this result are relevant for many fields of economic theory. It is first of all clear that if we choose to initialize the dynamics in the basin of attraction of this trapping region, a continuum of perfect foresight solutions may be observed. A simple econometric exercise, linking the physical-to-human capital ratio (state variable) to the 5-years forward variance of the growth rate of an unbalanced sample of 183 countries, seems to provide empirical backing for the phenomenon. Other important consequences, relevant from the point of view of endogenous cycles theory, are also scrutinized in the paper.

Denoising large-scale biological data using network filters

BackgroundLarge-scale biological data sets are often contaminated by noise, which can impede accurate inferences about underlying processes. Such measurement noise can arise from endogenous biological factors like cell cycle and life history variation, and from exogenous technical factors like sample preparation and instrument variation.ResultsWe describe a general method for automatically reducing noise in large-scale biological data sets. This method uses an interaction network to identify groups of correlated or anti-correlated measurements that can be combined or “filtered” to better recover an underlying biological signal. Similar to the process of denoising an image, a single network filter may be applied to an entire system, or the system may be first decomposed into distinct modules and a different filter applied to each. Applied to synthetic data with known network structure and signal, network filters accurately reduce noise across a wide range of noise levels and structures. Applied to a machine learning task of predicting changes in human protein expression in healthy and cancerous tissues, network filtering prior to training increases accuracy up to 43% compared to using unfiltered data.ConclusionsNetwork filters are a general way to denoise biological data and can account for both correlation and anti-correlation between different measurements. Furthermore, we find that partitioning a network prior to filtering can significantly reduce errors in networks with heterogenous data and correlation patterns, and this approach outperforms existing diffusion based methods. Our results on proteomics data indicate the broad potential utility of network filters to applications in systems biology.

Impacts of long-term inorganic and organic fertilization on phosphorus adsorption and desorption characteristics in red paddies in southern China.

Soil phosphorus (P) adsorption and desorption occur in an important endogenous cycle linked with soil fertility problems and relevant to the environmental risk assessment of P. In our study, the effect of long-term inorganic and organic fertilization on P adsorption and desorption characteristics in relation to changes in soil properties was evaluated by selecting three long-term experimental sites in southern China. The selected treatments at each site were CK (unfertilized), NPK (synthetic nitrogen, phosphorus and potassium) and NPKM (synthetic NPK plus manure). The adsorption and desorption characteristics of P were evaluated using Langmuir and Freundlich isotherms. The results showed that long-term application of NPK plus manure significantly increased soil organic carbon (SOC), total P and available P at all three sites compared with the NPK and CK treatments. All three treatments fit these equations well. The maximum adsorption capacity (Qm) of P increased with NPKM treatment, and the binding energy of P (K) and the maximum buffering capacity (MBC) showed increasing trends. NPKM showed the highest Qm (2346.13 mg kg-1) at the Jinxian site, followed by Nanchang (221.16 mg kg-1) and Ningxiang (2219.36 mg kg-1). Compared to CK and NPK, the NPKM treatment showed a higher MBC as 66.64, 46.93 and 44.39 L kg-1 at all three sites. The maximum desorption capacity (Dm) of P in soil was highest with the NPKM treatment (157.58, 166.76, 143.13 mg kg-1), showing a better ability to release P in soil. The correlation matrix showed a significant positive correlation of SOC, total and available P with Qm, Dm and MBC. In conclusion, it is suggested that manure addition is crucial to improve P utilization in red paddy soils within the recommended range to avoid the risk of environmental pollution.

Apicomplexan Protozoa Responsible for Reproductive Disorders: Occurrence of DNA in Blood and Milk of Donkeys (Equus asinus) and Minireview of the Related Literature.

Donkeys may be susceptible to many pathological agents and may act as carriers of pathogens for other animal species and humans. This study evaluated the occurrence of potentially abortifacient apicomplexan protozoa DNA in blood and milk samples collected at different time periods during lactation (1, 6, and 10 months) from 33 healthy dairy jennies. A total of 73 blood and 73 milk samples were used for DNA extraction and analysis. Blood specimens from 11/33 (33%) jennies scored positive for Theileria equi, while milk samples scored negative. Blood and milk of 3/33 jennies yielded DNA of Toxoplasma gondii at 6 months (n. 1) and 10 months (n. 2) after parturition. Neospora caninum DNA was found in four milk and in five blood samples only at one month after parturition. This study is the first report about the presence of N. caninum DNA in milk of naturally infected jennies. Moreover, the excretion of N. caninum DNA in some of these jennies at 30 days from the parturition may suggest a possible occurrence of an endogenous cycle, while the presence of T. gondii DNA in the milk collected at 6 and 10 months after parturition may be suggestive of a discontinuous excretion.

Deterministic debt cycles in open economies with flow collateral constraints

This paper establishes the existence of endogenous cycles in infinite-horizon open economy models with a flow collateral constraint. It shows that for plausible parameter configurations, the economy has a unique equilibrium exhibiting deterministic cycles in which periods of debt growth are followed by periods of debt deleveraging. In particular, three-period cycles exist, which implies by the Li-Yorke Theorem the presence of cycles of any periodicity and chaos. The paper also shows that deterministic cycles are absent in the Ramsey optimal allocation providing a justification for macroprudential policies even in the absence of uncertainty.

State Space Model to Detect Cycles in Heterogeneous Agents Models

We propose an empirical test to depict possible endogenous cycles within Heterogeneous Agent Models (HAMs). We consider a 2-type HAM into a standard small-scale dynamic asset pricing framework. On the one hand, fundamentalists base their expectations on the deviation of fundamental value from market price expecting a convergence between them. On the other hand, chartists, subject to self-fulling moods, consider the level of past prices and relate it to the fundamental value acting as contrarians. These pricing strategies, by their nature, cannot be directly observed but can cause the response of the observed data. For this reason, we consider the agents' beliefs as unobserved state components from which, through a state space model formulation, the heterogeneity of fundamentalist-chartist trader cycles can be mathematically derived and empirically tested. The model is estimated using the S&P500 index, for the period 1990-2020 at different time scales, specifically, daily, monthly, and quarterly.

Dynamic Dilemma of Political Distrust

While it has been argued that money politics magnifies political distrust, little is known about how political distrust affects money politics. To reveal this overlooked aspect, we first construct a static electoral competition model where two candidates propose policy platforms, and an interest group determines the number of campaign contributions for each candidate. We show that political distrust mitigates money politics; that is, in the presence of high political distrust, candidates do not propose a policy favored by the interest group. Based on this mechanism, we identify the dynamic dilemma of political distrust: political distrust improves future democratic performance, whereas it is a signal of past low performance. By extending the model to a dynamic one with short-lived players, we find that this dynamic dilemma could create endogenous cycles of political distrust and money politics when the misalignment of policy preferences between voters and the interest group is severe. Political trust is accumulated, consumed, and then restored, following cycles of money politics.

Endogenous business cycles with financial frictions

ABSTRACT This paper uncovers a series of belief shocks that drive the U.S. economy from both financial markets data and a financial accelerator model with self-fulfiling prophecies. Indeterminacy in the economy does not require externalities or increasing returns in production but it arises from an endogenous and countercyclical markup channel. The computed belief shocks are well identified and resemble the observable proxy in the real world. The model-driven solely by belief shocks performs well on replicating major U.S. business cycle facts. The belief-driven model contains a strong internal propagation mechanism and has more forecasting ability than a standard real business cycle model disturbed by technology shocks.

MOSAIC: a joint modeling methodology for combined circadian and non-circadian analysis of multi-omics data.

Circadian rhythms are approximately 24-h endogenous cycles that control many biological functions. To identify these rhythms, biological samples are taken over circadian time and analyzed using a single omics type, such as transcriptomics or proteomics. By comparing data from these single omics approaches, it has been shown that transcriptional rhythms are not necessarily conserved at the protein level, implying extensive circadian post-transcriptional regulation. However, as proteomics methods are known to be noisier than transcriptomic methods, this suggests that previously identified arrhythmic proteins with rhythmic transcripts could have been missed due to noise and may not be due to post-transcriptional regulation. To determine if one can use information from less-noisy transcriptomic data to inform rhythms in more-noisy proteomic data, and thus more accurately identify rhythms in the proteome, we have created the Multi-Omics Selection with Amplitude Independent Criteria (MOSAIC) application. MOSAIC combines model selection and joint modeling of multiple omics types to recover significant circadian and non-circadian trends. Using both synthetic data and proteomic data from Neurospora crassa, we showed that MOSAIC accurately recovers circadian rhythms at higher rates in not only the proteome but the transcriptome as well, outperforming existing methods for rhythm identification. In addition, by quantifying non-circadian trends in addition to circadian trends in data, our methodology allowed for the recognition of the diversity of circadian regulation as compared to non-circadian regulation. MOSAIC's full interface is available at https://github.com/delosh653/MOSAIC. An R package for this functionality, mosaic.find, can be downloaded at https://CRAN.R-project.org/package=mosaic.find. Supplementary data are available at Bioinformatics online.

Debt Resilience Dynamics: Exploring Vulnerability of Macrosystem

The article on the contemporary approach analysis of sovereign debt reveals the basic structures of national economy alternative financing. The methodology of system dynamics is applied to explain the sovereign debt burden pressure feedback process. The main effects of resilience to external shocks are explored. The problem of dynamic balancing between long-term economic development and short-term financial stability is detected. The analysis for borrowing capacity of the national economy is explored using the system dynamics methods. The resource curse “vicious cycle” should be overridden by increasing total factor productivity and decreasing sovereign debt. The main findings of the article concern the nonlinear relationships in the national economic debt system and reveal the issues of the sovereign debt trap enhanced by the resource type of economic development. The model developed in this article reflects the main role of innovations (total factor productivity growth) in coming out of the “resource curse” debt trap. The hypothesis that sovereign debt can be eliminated arises from the possibility of autonomous national economic development and endogenous business cycle stabilization. Such a point of view allows to capture the important interrelationships between the national economic development and external borrowings due to the concept of policy resistance implementation. It is indicated that the complex systems modeling likelihood to develop the sovereign debt policy for demonstration of the negative impact of debt trap on economic development. In order to achieve the results, issued in the article, a basic control loop model was developed using reference mode data with appropriate initial structure model construction. JEL classification: B22, C53, C61, E17, E5 Manuscript received 30.04.2020

The “New” Neoclassical International Political Economy of Macroprudential Regulation and Capital Controls: “Style” over “Substance”

A “new” neoclassical international political economy (NNIPE) emerged from the 2008 financial crisis showing how macroprudential regulation and capital controls (MPR-CC) can eliminate the systemic risk behind endogenous financial cycles. An implication of this is that decentralized capitalism is inherently financially unstable, which appears to make inroads with heterodox traditions. However, this paper demonstrates that NNIPE represents a superficial, rhetorical appearance of theoretical improvement, as represented in its “style,” while the “substance” of its underlying assumptions and mechanisms remain mired in neoclassicism. Moreover, it grew out of ideologically-motivated ideational change at the International Monetary Fund.

Lipoprotein metabolism with a focus on COVID 19 kidney patients

This article presents the role of lipids, apoproteins and lipoproteins and their metabolic pathways. Definition and function of fatty acids, triglycerides, phospholipids, cholesterol, chylomicron, VLDL, LDL, HDL, IDL and Lp (a) are described. Both exogenous and endogenous cycles of lipids and their metabolic pathways are presented and the roles of both lipoprotein lipase and hepatic lipase are included for means of better understanding. The major cardiovascular risk that LDL cholesterol represents is outlined as well as its atherogenic role. During the COVID 19 pandemic there are alterations in the lipid profile that worsen the risk. There is the decrease in HDL and LDL cholesterol fractions acutely during the infection, pointing out that the main deleterious effects are due to lipid changes mainly to HDL cholesterol diminution. As seen in the HDL’s role description, its protagonism in the reverse transport of cholesterol from the periphery to the liver, HDL particles have affinity for binding and neutralization of pathogen associated lipids that mediate the excessive immune reaction in sepsis. It is important to emphasize its already mentioned function in immunomodulation, antithrombosis and antioxidation, that are diminished with its lowering. Also lipoprotein lipase activity is lessened and thus VLDL particles and consequently triglycerides are increased. COVID 19 added to chronic kidney disease present repercussions and higher detrimental effects, not to mention its causative action in acute kidney disease. Lipoprotein metabolic changes can signalize to COVID 19 aetiology in kidney diseases.

0257 Preliminary Findings: Attentional Bias for Food Cues Unrelated to Time Awake or Circadian Phase During Forced Desynchrony in Adolescents

Abstract Introduction Sleep quantity and quality influence attentional bias, and attentional bias for food cues has been associated with body weight. Whether the endogenous circadian cycle and/or time from awakening to bedtime contribute to attentional bias for food and differences in weight remain unclear. Using a 28-h forced desynchrony (FD) design, we hypothesized that adolescents with overweight (OW) and obesity (O) would have more attentional bias for food cues later in the wake episode and at a later circadian phase compared to adolescents with a healthy weight (HW). Methods 50 (28 male) adolescents (12-15yr) completed 7 FD cycles. Participants completed an attentional bias task that included three food word categories (savory, sweet, fruits/vegetables) and one non-food word category (school supplies). The task was completed at 6 fixed times each cycle: Task 1 was 1.3h after scheduled awaking, Task 2 was 2h after Task 1, and Tasks 3–6 followed at 3-h intervals. Weight categorization used body mass index (BMI) percentiles (CDC): HW (>5th and <85th; n=24), OW (85th and <95th; n=13), or O (≥95th; n=14). Endogenous circadian period was determined using salivary melatonin onsets (Mean: HW=23.88h; OW=24.01h; O=23.86h). Effect of circadian phase and time since scheduled awakening was assessed by mixed effects modeling using 6 circadian and 6 time-awake bins. Results We found no significant differences between weight groups in attentional bias for any of the food categories (p’s >.05). We also saw no significant time awake effects or circadian influence on attentional bias, nor did time awake or circadian phase moderate the associations between weight category and attentional bias (p’s >.05). Conclusion Weight groups did not impact food-related attentional bias across the wake episode or circadian phase. Future directions will explore whether attentional bias for food types predicts food choice and food consumption in this study. Support DK101046

Estimating Nonlinear Business Cycle Mechanisms With Linear VARs: A Monte Carlo Study

Recent macroeconomic research has revived the idea of nonlinear endogenous business and financial cycles. This paper investigates how well linear vector-autoregressions (VARs) identify endogenous cycle mechanisms and cycle frequencies when the underlying process is a nonlinear limit cycle. We conduct Monte Carlo simulations on five different nonlinear models in which cycles are driven by the interaction of two state variables. We find that while linear VARs quantitatively underestimate the strength of the interaction mechanism, they successfully identify the qualitative presence of a cycle mechanism in the majority of cases. Cycle detection rates range between 55% and almost 100%. The detection rate is higher (i) when the nonlinearity does not directly affect the interaction mechanism and (ii) the larger the strength of the interaction mechanism. Our results further suggest that linear VARs are relatively robust to false positives and are surprisingly successfully at estimating cycle frequencies of nonlinear processes. Overall, our findings suggest that linear VARs can be a useful tool to explore cyclical interactions even when the underlying process is nonlinear.