Contemporaneous Effects Research Articles

Whole-Brain Causal Discovery Using fMRI

Abstract Despite significant research, discovering causal relationships from fMRI remains a challenge. Popular methods such as Granger Causality and Dynamic Causal Modeling fall short in handling contemporaneous effects and latent common causes. Methods from causal structure learning literature can address these limitations but often scale poorly with network size and need acyclicity. In this study, we first provide a taxonomy of existing methods and compare their accuracy and efficiency on simulated fMRI from simple topologies. This analysis demonstrates a pressing need for more accurate and scalable methods, motivating the design of Causal discovery for Large-scale Low-resolution Time-series with Feedback (CaLLTiF). CaLLTiF is a constraint-based method that uses conditional independence between contemporaneous and lagged variables to extract causal relationships. On simulated fMRI from the macaque connectome, CaLLTiF achieves significantly higher accuracy and scalability than all tested alternatives. From resting-state human fMRI, CaLLTiF learns causal connectomes that are highly consistent across individuals, show clear top-down flow of causal effect from attention and default mode to sensorimotor networks, exhibit Euclidean distance-dependence in causal interactions, and are highly dominated by contemporaneous effects. Overall, this work takes a major step in enhancing causal discovery from whole-brain fMRI and defines a new standard for future investigations.

Contemporaneous and lagged spillovers between agriculture, crude oil, carbon emission allowance, and climate change

In this paper, we examine the contemporaneous and lagged spillovers among the agricultural, crude oil, carbon emission allowance, and climate change markets. Adopting the R2 decomposed connectedness approach, our empirical analysis reveals several key findings. First, the overall total connectedness index (TCI) dynamics have been mainly dominated by contemporaneous effects. Second, there are heterogeneous spillover effects among agricultural markets. Specially, corn, soybean meal, and wheat are the major risk transmitters to this system, while barley, cocoa, and lean hog are the main risk receivers of shocks. Third, we also find that climate change has significant spillovers to other markets.

An experimental test of eco-evolutionary dynamics on rocky shores.

A growing body of theoretical studies and laboratory experiments has focused attention on reciprocal feedbacks between ecological and evolutionary processes. However, uncertainty remains about whether such eco-evolutionary feedbacks have an important or negligible influence on natural communities. Thus, recent discussions call for field experiments that explore whether selection on phenotypic variation within populations leads to contemporaneous effects on community dynamics. To help fill this gap, in this study, we test the hypothesis that selection on consumer traits in a population of predatory drilling snails can drive eco-evolutionary dynamics in a rocky intertidal community in California, USA. We first conducted a laboratory selection experiment to raise newly hatched dogwhelks (Nucella canaliculata) on four diet treatments encompassing a range of prey species and shell thicknesses. Snails that survived to adulthood under these diet treatments differed in their capacity to drill thick-shelled mussels. Dogwhelks from these treatment groups were then outplanted to intertidal field cages for 1 year to test whether groups experiencing selection differed in their effects on mussel bed succession. As expected, succession proceeded most rapidly in the reference treatment with dogwhelks excluded. However, successional patterns differed minimally among dogwhelks raised under the different diet treatments. Thus, although our laboratory results suggest that prey can impose selection that leads to rapid adaptation and divergent consumer traits, these feedbacks were not strong enough to result in clear community effects in the field. We propose that a limited range of variation in functional traits within populations, moderate strengths of selection, and a background of substantial abiotic and biotic variation may all act to dampen the potential for strong eco-evolutionary dynamics in this and many other natural communities.

Within-person relationships between catastrophizing and pain intensity during a mind-body intervention to prevent persistent pain and disability after acute traumatic orthopedic injury

Interventions aimed at preventing chronic pain after acute traumatic injury have significant potential to reduce healthcare expenditures and improve quality of life for millions of individuals. Given recent development of such interventions, limited research has examined mechanisms of change using repeated measures (e.g., session-by-session assessments). This study examines within-person relationships between pain catastrophizing and intensity during and after a four-session mind-body intervention for individuals with acute traumatic orthopedic injury (N = 76, T = 445). Random intercept cross-lagged panel models were used to examine within-person autoregressive, contemporaneous, and cross-lagged effects between pain catastrophizing and pain intensity, after accounting for stable between-person differences. Our primary hypothesis that improvements in catastrophizing would be associated with subsequent reductions in pain intensity was partially supported by a significant within-person cross-lagged effect between catastrophizing at post-test and pain with activity reported at three-month follow-up (β = 0.421, SE = 0.099, p < .001). Improvement in catastrophizing was also associated with same-session improvement in pain intensity midway through the intervention. Importantly, bidirectional within-person analyses allowed us to rule out the possibility that improvements in pain were responsible for subsequent improvements in catastrophizing, but not vice versa. Together, these findings suggest improvements in catastrophizing during psychosocial intervention may prevent transition from acute to chronic pain after injury. Future research with larger between-person sample sizes, more frequent within-person assessment, and comparable control group data is necessary to facilitate greater understanding of psychosocial mechanisms for preventing chronic pain after injury. PerspectiveThis study examines within-person relationships between pain catastrophizing and intensity during and after a four-session mind-body intervention to prevent persistent pain after acute traumatic orthopedic injury. Improved catastrophizing at post-test was associated with reduced pain with activity at three-month follow-up. Within-person analyses enhance understanding of psychosocial mechanisms for preventing chronic pain after injury.

Have the causal effects between equities, oil prices, and monetary policy changed over time?

We reexamine the contemporaneous causal effects between the U.S. stock prices, crude oil prices, and monetary policy from 2005 to 2022. Our study offers two main contributions. First, we generalize a novel identification approach based on exogenous intraday shifts in the volatility in futures markets from two markets to multiple markets. Second, we examine contemporaneous causal effects between the U.S. stock prices, crude oil prices, and monetary policy. We show that the coefficients measuring contemporaneous causality have substantially changed over time. Specifically, we find that since 2008 stock returns affect crude oil returns. This time variation is also evident in the effect of monetary policy on the crude oil returns. We show that this time variation is consistent with two explanations: the zero lower bound (ZLB) and increased synchronization of crude oil prices with the business cycle.

Monumental effects: Confederate monuments in the Post-Reconstruction South

This paper explores the contemporaneous effects of Confederate monuments dedicated in the Post-Reconstruction South. I combine monument, election, and census data to create an election-year panel dataset of former Confederate counties between 1878–1912, then exploit the temporally staggered and geographically distributed dedication of monuments using a generalized difference-in-differences design. I find that monuments caused increases in Democratic Party vote share and decreases in voter turnout, with less robust decreases in Black population share. I find some evidence that more intense monument-building is associated with a decrease in Black lynchings. I also find varying effects based on the era of monument dedication, the intensity of monument-building, and monument characteristics. To address potential mechanisms, I present evidence that monuments were associated with increased use of famous Confederate names for children and show that decreases in voter turnout occurred exclusively in areas with larger Black population shares. Overall, my results suggest monuments promoted a distorted view of Civil War history that primarily persuaded southern whites, but also contributed to Black political suppression. The findings have implications for current debates over Confederate monuments in the United States.

Unveiling the drivers of banks' misconduct: Sanctions, signals, and the extent of unethical behaviour

This paper seeks to enhance our understanding of the drivers of misconduct in the banking sector. We propose several metrics of misconduct that allow for the identification of the occurrence, number and types of the breaches in the year in which they occur, rather than on the year in which the penalty is paid. Focusing on the US banking industry, our findings have important policy implications. We find that sanctions have a contemporaneous deterrent effect on misconduct. Large sanctions levied on large banks are also found to improve behaviour across the banking industry. The behaviour of larger banks acts as an informational signal for other banks, affecting their probability and intensity of misconduct.

Multilayer network analysis of idiosyncratic volatility connectedness: Evidence from China

This paper proposes multilayer networks, including lagged, contemporaneous, and long-run networks, to examine the idiosyncratic connectedness among Chinese financial institutions. We explore the topology of multilayer networks through static and dynamic analysis to capture the information transmission mechanism of idiosyncratic risks. Moreover, we investigate the drivers influencing idiosyncratic connectedness across financial institutions. We find that idiosyncratic risk contagion among financial institutions is stronger in the long-run network. At the same time, we note that the three networks contain different connection structures, which means that the information transmission mechanism of idiosyncratic risks is heterogeneous in multilayer networks. In addition, when the financial system is under stress, we observe that the contemporaneous effect of idiosyncratic connectedness rises rapidly. Institutional level analysis shows that diversified financial institutions play active roles in the lagged network, securities institutions are transmitters of contemporaneous information spillovers, and banking institutions are the main drivers of the long-run network. Finally, our study shows that size is the main factor driving idiosyncratic risk spillovers among financial institutions.

Does Valuing Happiness Lead to Well-Being?

Happiness has become one of the most important life goals worldwide. However, does valuing happiness lead to better well-being? This study investigates the effect of valuing happiness on well-being using a population-based longitudinal survey of Dutch adults (N = 8,331) from 2019 to 2023. Random-intercept cross-lagged panel models indicated that those who valued happiness generally exhibited higher well-being as manifested by life satisfaction, more positive affect, and less negative affect. However, increases in valuing happiness did not result in changes in life satisfaction 1 year later and had mixed emotional consequences (i.e., increasing both positive and negative affect). Additional analyses using fixed-effects models indicated that valuing happiness had contemporaneous positive effects on well-being. These findings indicate that endorsing happiness goals may have immediate psychological benefits but may not necessarily translate into long-term positive outcomes.

Performance modeling of composite fading channels: an application to wearable wireless communication systems

In pragmatic wireless propagation scenarios, communication between wearable devices may be significantly impacted by fading, particularly when wireless communication is crucial for mission control, situational awareness, and team coordination in defense operations. There may be times when communication links are temporarily unavailable in places due to contemporaneous effect of slow fading and fast fading, including cities or regions with tough terrain. This phenomena results in composite fading environments. Moreover, the data transfer speeds may drop as a result of fading, making it a challenging task to rapidly transmit crucial real time data. In addition, the precision of GPS and positioning systems, that are essential for operations viz., target tracking, navigation and rescue can be impacted by fading. In this setting, the work portrays modeling the fading channels over the Weibull distribution by exploiting Tsallis’ q-statistical framework. From the analytical observations, it was evident that in contrast to the well-known composite models, the q-Weibull model provides a better characterization of the generated fading signals. Furthermore, the closed form solution to the different performance metrics that are crucial in characterizing the fading environments are provided.

Evaluating the Effects of Public Debt on Sri Lanka’s Economic Growth: A Short-term and Long-term Perspective

Aims: The objective of this paper is to examine whether public debt enhances economic growth in Sri Lanka by separating debt into domestic and external debt. Study Design: The paper adopts the Keynesian demand-side model to estimate GDP on demand-side and supply-side factors such as domestic debt, external debt, gross fixed capital formation (investment in short), labour force, general price level, money supply, government spending and trade openness. In a model where debt causes investment, public debt effects are netted out from investment by removing the estimated investment effects of domestic and external debt. Duration of Study: quarterly data from Q1 2010 to Q1 2023 are utilized to trace the long-term and the short-term effects of domestic and external debt on GDP. Methodology: The ARDL method of estimation is used and the model is estimated in double log form so that estimated parameters reflect output elasticities. A general to specific modelling approach is adopted to find the best suited model. Results: Variables such as government spending, money supply, general price level and labour force are not relevant while domestic debt, external debt, investment (debt effects netted out) and trade openness are significant in describing GDP. The long-term domestic debt elasticity of GDP is 0.588 while short-term domestic debt elasticity (sum of contemporaneous and lag effects) is about 0.63. The cumulative effects of domestic debt on GDP tappers off to 0.60 in the long-run. The result suggests negative impacts (-0.272 and -0.254) of external debt on the economic growth in short-term and long-term respectively. The negative effect of external debt can be justified if recent external borrowings have been used to repay loans taken to finance war and unproductive projects. Conclusion: The paper finds that the domestic public debt creates relatively strong positive effects on GDP in the short-term and the long-term. Contrary to the expectations, the effects of external debt on GDP have become negative both in the short-term and the long-term. The paper also finds that debt effects on GDP have been significantly reduced when debt effect-ridden investment variable is included in the regression in place of debt-effect netted out investment. Thus, this study recommends researchers to carry out further research on why the effects of external debt on GDP become negative. Further, it recommends policy makers to use both domestic and external debt to finance public investment and productivity enhancement projects rather than borrowing merely for the purpose of consumption and repaying of existing debt.

The importance of sampling frequency for estimates of well-being dynamics

Using a high-frequency panel survey, we examine the sensitivity of estimated self-reported well-being (SWB) dynamics to using monthly, quarterly, and yearly data. This is an important issue if SWB is to be used to evaluate policy. Results from autoregressive models that account for individual-level heterogeneity indicate that the estimated persistence using yearly data is near zero. However, estimated persistence from monthly and quarterly data is substantial. We estimate that persistence to shocks typically lasts around six months and has a net present value of 75–80 per cent of the contemporaneous effect. Estimates are similar for different domains of SWB.

Dynamic ESG Equilibrium

This paper proposes a conditional asset pricing model that integrates environmental, social, and governance (ESG) demand and supply dynamics. Shocks in the demand for sustainable investing represent a novel risk source, characterized by diminishing marginal utility and positive premium. Green assets exhibit positive exposure to ESG demand shocks, hence commanding higher premia. Conversely, time-varying convenience yield leads to lower expected returns for green assets. Moreover, ESG demand shocks have positive contemporaneous effects on unexpected returns, contributing to large positive payoffs in the green-minus-brown portfolio over extended horizons. The model predictions align closely with evidence on return spreads between green and brown assets, further reinforcing the apparent gap between realized and expected spreads. This paper was accepted by Lin William Cong, finance. Funding: Y. Liu acknowledges funding by the Research Grants Council of the Hong Kong Special Administrative Region, China [Grant T35/710/20R]. A. Tarelli acknowledges funding by the European Union - Next Generation EU [Project Code 2022FWZ2CR]. The views and opinions expressed are only those of the authors. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03491 .

The blind spot in residential mortgages: Increasing default option value in the face of declining house prices

The interest rate hikes intended to combat inflation have not only significantly increased mortgage payments, but also significantly depressed house prices. The probability of default for mortgages is typically estimated through the debt servicing ability of the obligor. The alternative estimation based on the default option, although well studied in literature, is typically not used by practitioners. This option is normally ‘deep out of money’ and moves in the money if the loan to value (LTV) increases significantly, even creating negative equity. This is typically a remote probability due to the down payment requirements, but not as much under the current environment, where the house price depreciation has significantly increased LTVs, especially for newer mortgages underwritten when house prices were at their peak. This paper discusses the potential risk management oversights in this environment, illustrating that the increasing default risk is not adequately captured in probability of default (PD) models based on debt servicing ability alone. This is also true for the loss given default (LGD) risk if the contemporaneous LTV effects are not captured. Numerical examples are provided to demonstrate the material increase in PD, LGD and the combined expected loss risk with increasing LTV. It also discusses an alternative default option PD model, its calibration and its usage for stress testing along with LGD modelling, which together capture the contemporaneous LTV effects.

Can cross-lagged panel modeling be relied on to establish cross-lagged effects? The case of contemporaneous and reciprocal effects.

This article considers identification, estimation, and model fit issues for models with contemporaneous and reciprocal effects. It explores how well the models work in practice using Monte Carlo studies as well as real-data examples. Furthermore, by using models that allow contemporaneous and reciprocal effects, the paper raises a fundamental question about current practice for cross-lagged panel modeling using models such as cross-lagged panel model (CLPM) or random intercept cross-lagged panel model (RI-CLPM): Can cross-lagged panel modeling be relied on to establish cross-lagged effects? The article concludes that the answer is no, a finding that has important ramifications for current practice. It is suggested that analysts should use additional models to probe the temporalities of the CLPM and RI-CLPM effects to see if these could be considered contemporaneous rather than lagged. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Heterogeneous peer effects under endogenous selection: An application to local and migrant children in elementary schools in Shanghai

This paper develops a model that allows for heterogenous contemporaneous peer effects among different types of agents who are endogenously selected into different peer groups. We apply our approach to migrant and local students in Shanghai, where local students all go to public schools, but migrant students are endogenously selected into either public schools or lower-quality private schools. The results suggest large contemporaneous peer effects among all student groups. We conduct policy experiments to examine the effect of transferring migrant students from private schools to public schools, and show that peer effect can be substantially more important than the school effect.

Heterogeneity in suicide risk: Evidence from personalized dynamic models

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

Cracking Chicken-Egg Conundrums: Juxtaposing Contemporaneous and Lagged Reciprocal Effects Models of Academic Self-Concept and Achievement’s Directional Ordering

Multi-wave-cross-lagged-panel models (CLPMs) of directional ordering are a focus of much controversy in educational psychology and more generally. Extending traditional analyses, methodologists have recently argued for including random intercepts and lag2 effects between non-adjacent waves and giving more attention to controlling covariates. However, the related issues of appropriate time intervals between waves (lag1 intervals across waves) and the possibility of contemporaneous (lag0) effects within each wave are largely unresolved. Although philosophers, theologians, and scientists widely debate sequential (lagged) and simultaneous (lag0) theories of causality, CLPM researchers have mostly ignored contemporaneous effects, arguing causes must precede effects. In a substantive-methodological synergy, we integrated these issues and designed new structural equation models to reanalyze one of the strongest CLPM studies of academic self-concept (ASC) and achievement (five annuals of mathematics data; 3527 secondary school students). A taxonomy of models incorporating various combinations of lag0, lag1, and lag2 effects, random intercepts, and covariates consistently supported a priori reciprocal effect model (REM) predictions—medium or large reciprocal effects of ASC and achievement on each other. Consistent with self-concept theory, effects of ASC on achievement evolved over time (lag1, not lag0 effects), whereas effects of achievement on ASC effects were more contemporaneous (lag0, not lag1 effects). We argue that lag0 effects reflect proximal events occurring subsequent to the previous data wave, suggesting the need for shorter intervals but also leaving open the possibility of contemporaneous effects that are truly instantaneous. We discuss limitations and future directions but also note the broad applicability of our statistical models.

Odyssean forward guidance in normal times

We present a systematic treatment of dynamic effects of Odyssean forward guidance – explicit announcements about future policy rates. We focus on normal times unlike the mainstream of the literature that focuses on episodes of an effective (zero) lower bound on nominal interest rates. We present novel closed-form solutions to both deterministic and stochastic versions of a stylized new Keynesian model with fully anticipated future shocks. We establish a theorem that delineates the parameter space into real and complex-root regions characterized by different characteristic roots. We formulate a simple recipe for testing the effectiveness of forward guidance: the size of the smallest root is a single sufficient statistics that determines whether or not forward guidance generates significant contemporaneous effects.

Supplemental Material for Can Cross-Lagged Panel Modeling Be Relied on to Establish Cross-Lagged Effects? The Case of Contemporaneous and Reciprocal Effects

Supplemental Material for Can Cross-Lagged Panel Modeling Be Relied on to Establish Cross-Lagged Effects? The Case of Contemporaneous and Reciprocal Effects