This paper presents the first study to investigate ethnic differential treatment in public housing through a correspondence test field experiment. The experiment involved sending inquiries from fictitious couples with Swedish or Arabic names to all public housing companies in Sweden. Four outcomes were examined: whether the public housing companies responded to the inquiries, whether they initiated their response with a greeting, whether they had a priority system in place, and whether they provided information about problematic neighborhoods. The findings revealed disparities in the treatment of the couples. The Swedish couple received greetings and information about problematic neighborhoods at a greater rate than the Arab couple. This study contributes to existing literature on ethnic differences in the housing market by providing evidence of differential treatment within the public housing sector. Additionally, it explores the content and quality of public housing companies' responses, offering valuable insights for policymakers and housing professionals in designing interventions to promote equality and counteract differential treatment.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.

Exchange rate modeling has always fascinated researchers because of its complex macroeconomic dynamics. This study documents the exchange rate dynamics of major emerging economies after accounting for their macroeconomic cycles and explores the Bayesian Vector Error Correction Model (VECM) Markov Regime switching model, which uses time-varying transition probabilities. The main objective is to study the exchange rate dynamics of Brazil, Russia, India, China, and South Africa (BRICS) vis-a-vis the US dollar. The Bayesian setup uses two hierarchal shrinkage priors, the normal-gamma (NG) prior and the Litterman prior, for parameters' estimation. These shrinkage priors allow for a more comprehensive assessment of the regime-specific coefficients. The model performed well in differentiating between the two regimes for all currencies. The Russian ruble was identified to be the most depreciated currency, whereas the African Rand was the most appreciated. The evaluation of model features revealed that many regime-specific coefficients differed significantly from their common mean. A forecasting exercise was then performed for the out-of-sample period to assess the model's performance. A significant improvement was observed over the basic random walk (RW) model and the linear Bayesian vector autoregression (BVAR) model.

Introduction: Saving is a journey, beginning with the critical decision to initiate the process, take that pivotal first deposit step, and persistently commit to ongoing savings. However, a lot of saving plans fail already before any deposit is made, and even if the first deposit is made, long-run success of savings is far from guaranteed. In this study, we investigate both individual and saving-goal-specific determinants of successful savings.

Method: We use real-life savings data (N = 2,619 saving goals of 808 individuals) from a FinTech company in Sweden that helps individuals save for their goals. In addition, we collect a wide range of individual characteristics related to financial behavior: individuals' objective and subjective financial knowledge, self-control, and information avoidance.

Results and discussion: Our analysis uncovered distinctive patterns at different stages of the saving process. While objective financial knowledge didn't correlate with how much one saves, it was significantly related to the likelihood of making the first deposit. Furthermore, individuals with high self-control exhibited greater savings, though self-control was not related to the initiation of saving. Interestingly, subjective financial literacy and information avoidance showed no significant association with overall savings behavior. Additionally, our study indicated that the attainability of goals plays a crucial role in depositing funds, with more achievable goals having higher deposit likelihoods. Conversely, ambitious goals, despite their challenging nature, tended to attract more substantial savings. Our findings, grounded in real-life data, provide valuable insights into the intricate mechanisms influencing successful saving behaviors, shedding light on the complexities of financial decision-making and goal pursuit.

This study explores the interconnectedness of bond markets in the Association of Southeast Asian Nations (ASEAN-4: Indonesia, Malaysia, the Philippines, and Thailand) with significant regional and global markets, focusing on transmitting global shocks to these markets. The analysis is based on the forecast error variance decomposition (FEVD) of a vector autoregression (VAR) model and wavelet-based longer horizon approaches, enabling us to identify the net transmitter and receiver of return and volatility shocks among the underlying markets at various investment horizons. In addition, we evaluate the primary drivers of ASEAN-4 bond markets, employing global and ASEAN-4 macroeconomic indicators and uncertainty measures to explain variations in the spillover dynamics. Empirical findings reveal strong inter-country connectedness among bond markets, with the U.S. market having the most significant links for 7- and 10-year bond maturities. However, there is limited connectedness within ASEAN-4 and other developing countries, indicating strong diversification potential. Furthermore, our findings indicate increased interconnectedness during COVID-19 and that macroeconomic fundamentals significantly influence the ASEAN-4 markets, rationalizing the heterogeneous cross-border transmission of uncertainty shocks. The findings contribute to the literature on bond market spillovers, offering valuable insights for policymakers, regulators, and investors seeking portfolio diversification, risk management, and sustainable growth in the ASEAN-4 markets.

Bounded ethicality refers to people’s limited capacity to consistently behave in line with their ethical standards. Here, we present results from a pre-registered, large-scale (N = 11,050) survey of researchers in Sweden, suggesting that researchers too are boundedly ethical. Specifically, researchers on average rated themselves as better than other researchers in their field at following good research practice, and rated researchers in their own field as better than researchers in other fields at following good research practice. These effects were stable across all academic fields, but strongest among researchers in the medical sciences. Taken together, our findings illustrate inflated self-righteous beliefs among researchers and research disciplines when it comes to research ethics, which may contribute to academic polarization and moral blindspots regarding one’s own and one’s colleagues’ use of questionable research practices.

The study presented in this paper examined intersectional discrimination against individuals with multiple minority identities in the housing market, specifically those identifying as Arab Muslims. By sending inquiries from three fictitious applicants - a Swedish Christian, an Arab Christian, and an Arab Muslim - to 1,200 landlords in Sweden, we analyzed differences in landlord responses. Results showed the Swedish Christian received the most positive replies, followed by the Arab Christian, with the Arab Muslim receiving the fewest. The study underscores the compounded discrimination faced by those with multiple minority identities and challenges the conflation of ethnic and religious identities in prior research.

While numerous empirical papers have investigated the volatility dynamics of Chinese clean energy equity markets, this is among the first studies to assess the impact of climate uncertainty on the risk levels of such assets. Given that China is extensively investing in green projects to achieve carbon neutrality, this strand of research offers important implications for investors and policymakers. Methodologically, we employ the GARCH-MIDAS model to examine the effect of the climate policy uncertainty (CPU) index on the volatility levels of the Chinese clean energy exchange-traded fund (ETF). We compare the effects of the CPU index with leading uncertainty indicators, including the crude oil volatility index, geopolitical risk, and technology sector volatility. The in-sample and out-of-sample analyses show that CPU has significant predictive contents for forecasting the volatility of renewable energy ETF and that the GARCH-MIDAS-CPU process outperforms other approaches. These results offer key implications for policymakers and socially responsible investors.

We investigate whether corporates' environmental, social, and governance (ESG) performance affects their systemic risk. Based on 284 publicly-listed Chinese firms over the period 2011-2020, we construct a tail risk spillover network for measuring their connectedness and systemic risk and use a panel regression model to examine the influence of corporate ESG performance on systemic risk. Network connectedness is an essential channel for risk contagion, and the energy, industry, and finance sectors occupy a significant position in the system. The ESG performance has a significant negative impact on systemic risk, both in terms of systemic vulnerability and systemic risk contribution, i.e., the ESG performance can dampen the two-way transmission of shocks between individual firms and the system. The results are robust to proxy measures of systemic vulnerability and systemic risk contribution, as well as to winsorize all variables and lag the core explanatory variables. Our study provides a new angle from the ESG performance for regulating systemic risk.

How can people lead fulfilling lives both thanks to and despite the constant use of digital media and artificial intelligence? While the prevailing narrative often portrays these technologies as generally harmful to well-being, the reality is of course more nuanced—some individuals benefit, while others do not. Existing research has predominantly focused on the general consequences of digital media on well-being, with less attention given to the individual-level antecedents of digital well-being. In the present study, we aimed to identify the traits and characteristics of individuals who use digital tools in ways that promote their well-being. Using a large representative sample from Sweden (N = 1999), we explore how digital self-control, digital literacy (objective and subjective), and digital information ignorance predict digital well-being, life satisfaction, and social anxiety. Digital self-control and subjective digital literacy positively predicted digital well-being. Digital self-control also predicted greater life satisfaction. Finally, digital information ignorance predicted increased life satisfaction and social anxiety. Overall, the current study contributes to a growing literature on digital well-being by exploring its antecedents.

Following the outbreak of novel coronavirus, numerous studies have assessed the effect on global financial markets. However, investigations into whether, and to what extent, dirty and clean energy asset classes are sensitive to contagious diseases are rare. This study aims to fill this gap in the literature. We measured the effects of contagious viruses using the recently introduced infectious disease-related uncertainty index (EMVID). Our data include the iShares Global Energy ETF and clean energy stock indices from leading economies such as the United States, the European Union, Japan, and China. Employing the GARCH-MIDAS model, we find that the uncertainty associated with infectious diseases has a significant positive (negative) effect on the realized volatility (RV) of dirty (green) assets. This finding is novel given that it indicates the potential for "green recovery" in the post-pandemic era. Our findings further document that EMVID has significant predictive content for the volatility of these assets and that inserting the EMVID index into the GARCH-MIDAS process produces better volatility predictions than other uncertainty measures, including the crude oil volatility (OVX), geopolitical risk (GPR), and economic policy uncertainty (EPU) indices. Hence, the EMVID provides additional information not contained in the OVX, GPR, or EPU during the pandemic period. Our findings will be useful for energy market participants to make appropriate asset allocation decisions during pandemics.

This paper examines the relationship between firms' sustainability practices and their value during a crisis when overall trust and support are lacking in the economy. While a handful of studies explore this research agenda concentrating on the US context and a standalone crisis, we provide novel evidence on the Asia Pacific region considering three global crises. Applying difference-in-differences regressions, we find that high-sustainability companies posted superior value during the global financial crisis and the European debt crisis. This result, however, does not hold for the COVID-19 crisis. This key finding passes several endogeneity tests (firm-fixed effect, propensity score matching, and post-crisis interaction). As we explore potential mechanisms of firm resistance during crises and apply a triple difference approach, we find evidence that firm value was intensified during the crises due to sustainability activities coupled with high customer loyalty, high institutional ownership, and a low degree of information asymmetry. Finally, although high sustainability performance generally positively impacted firm value during crises, this relationship was negative (weaker) for the highly impacted industries (the emerging countries) included in the sample. Our key finding continues to hold for a set of robustness checks. The outcome of this study provides significant policy directions to regulators, corporate managers, and investment professionals.

Both theory on motivational crowding and recent empirical evidence suggest that nudging may sometimes backfire and actually crowd out prosocial behavior, due to decreased intrinsic motivation and warm glow. In this study, we tested this claim by investigating the effects of three types of nudges (default nudge, social norm nudge, and moral nudge) on donations to charity in a preregistered online experiment (N = 1098). Furthermore, we manipulated the transparency of the nudges across conditions by explicitly informing subjects of the nudges that were used. Our results show no indication that nudges crowd out prosocial behavior; instead, all three nudges increased donations. The positive effects of the nudges were driven by the subjects who did not perceive the nudges as attempts to manipulate their behavior, while donations among subjects who felt that the nudges were manipulative remained unaffected. Subjects’ self-reported happiness with their choice also remained unaffected. Thus, we find no indication that nudges crowded out warm glow when acting altruistically. Generally, our results are good news for the proponents of nudges in public policy, since they suggest that concerns about unintended motivational crowding effects on prosocial behavior have been overstated.

According to the Schumpeterian cleansing hypothesis, economic downturns force inefficient firms off the market, freeing resources that can be allocated to more efficient firms. India, as an emerging economy, may experience a similar reallocation. The study uses micro-level data for publicly traded firms, including manufacturing and services sector firms, from 1988 to 2020. We find that reallocation is productivity-enhancing in general, i.e., credit moves from firms with low productivity to firms with high productivity, and normal economic downturns induce this efficiency-enhancing reallocation. We also observe that reallocation is less efficiency-enhancing during the Indian financial crisis, and constraints on productive firms could be one of the potential explanations for the lack of a cleansing effect.

Although the US transport sector is one of the major users of fossil fuel (e.g., crude oil), the impact of energy price volatility on transport stock sector indexes remains under-researched. The present study addresses this research void by investigating the impact of energy implied volatility on transportation stock returns in the US. Using the crude oil volatility index (OVX), as a proxy of energy price volatility, and three Dow Jones indexes tracking the performance of the airlines, marine and trucking stock subsectors, we employ a GARCH-jump model. The main results show that the oil market sends volatility to the US transport subsector stock indexes, suggesting that oil implied volatility plays a role in pricing US transport stocks. The impact of OVX shocks is asymmetric, indicating that increases and decreases in oil implied volatility have a heterogeneous impact on the transport subsector stock markets. Jumps are significant in the three transport subsector stock indexes, and are time-dependent. Notably, the three transportation subsector stock indexes are more sensitive to OVX shocks than the S&P 500 index. These results have important implications for investors, policymakers, academics, and managers of the US transportation industry.

In this paper, we estimate fuel price elasticities of sailing speed for general cargo vessels using data covering the Baltic Sea and Norwegian coastal areas during the years 2007-2018. To disentangle the correlation between fuel prices and freight rates arising from changes in global demand, we instrument fuel prices on price changes triggered by supply shocks. The shocks are derived from the structural vector autoregressive (SVAR) model proposed by Kilian (2009). In a sensitivity analysis, we use unanticipated oil supply shocks derived from oil supply outages as an alternative instrument for fuel prices. We find that disregarding the correlation between fuel prices and freight rates yields biased parameter estimates, which can partly explain the mixed results in the previous literature. Our preferred estimate for the fuel price elasticity of speed is -0.08.

Den globala finanskrisen 2007–2009 har gett oss två viktiga lärdomar. Först och främst belyste krisen hur viktigt det är att förstå bostadsmarknaders drivkrafter och dess kopplingar till andra ekonomiska sektorer. För det andra visade finanskrisen hur störningar som uppstår på finansmarknaderna kan påverka resterande delar av ekonomin. Denna avhandling syftar till att ge nya empiriska insikter kring den komplexa dynamik och de drivkrafter som är associerade med bostadsmarknader. Avhandlingen syftar också till att skapa mer förståelse för hur finansiella fluktuationer kan påverka den svenska makroekonomin.   

Avhandlingen kan anses karaktäriseras av begreppet heterogenitet. Till exempel har flera kapitel fokuserat på hur olika regioner och sektorer påverkats av makroekonomiska variabler och/eller chocker. I studierna undersöks också effekten på olika bostadstyper, samt så belyses utfall hos variabler som tidigare fått begränsad uppmärksamhet i litteraturen. Avhandlingen består av fem separata kapitel/artiklar som behandlar olika aspekter relaterade till bostadsmarknaden eller hur finansiella chocker påverkar makroekonomin.  

I det första kapitlet studeras sambandet mellan priser på energiråvaror (olja, kol och naturgas) och nio regionala bostadsmarknader i USA. Istället för att endast undersöka sambandet mellan oljepriset och bostadsmarknaden, så adderar studien till litteraturen genom att inkludera ytterligare energiråvaror.  I studien används metoder som syftar till att mäta icke-linjära samband.    

I det andra kapitlet undersöker vi effekten av energieffektivitet på försäljningspriset för bostadsrätter i Sverige. Trots ett omfattande antal studier om hur energieffektivitet påverkar försäljningspriset för villor, så har ingen tidigare studie enbart fokuserat på bostadsrätter. Resultaten visar blandade effekter av energieffektivitet på försäljningspriser. Studien indikerar att det kan finnas ett behov av mer riktade åtgärder, om målet är att bostadsköpare ska beakta energieffektivitet vid köp av bostadsrätter.   

I det tredje kapitlet används en Panel VAR (Panel Vector Autoregression) med interaktionsvariabler (IPVAR) för att analysera om institutionella faktorer, d.v.s. storleken på hyresmarknaden och hyresmarknadsregleringar, kan förklara hur bostadsmarknader i olika länder reagerar på makroekonomiska chocker.

I det fjärde kapitlet används strukturella VAR-modeller (Bayesianska och faktor-augmenterade) i syfte att ge en omfattande översikt över hur finansiella chocker påverkar den svenska arbetsmarknaden. Istället för att endast fokusera på hur finansiella chocker påverkar arbetsmarknaden på nationell nivå, så undersöker studien även effekterna på regioner och sektorer. Resultaten tyder på en omfattande variation i respons inom olika sektorer och mellan regioner.     

I det femte kapitlet används, precis som i det fjärde, VAR-modeller i syfte att undersöka hur finansiella chocker påverkar den svenska bostadsmarknaden (på nationell samt regional nivå). Studien finner att finansiella chocker tenderar att påverka bostadspriser mer än påbörjad byggnation av nya bostäder eller bygglov. Från den regionala analysen indikerar resultaten att huspriser i vissa områden är mer känsliga för finansiella chocker än andra. Priser i områden med oelastiskt utbud reagerar starkare än de i elastiska områden, även om detta fynd är högst beroende av hur VAR-modellen är specificerad.    

In the context of the rapidly growing demand for green investments and the need to combat climate change, this study contributes to the emerging literature on green investments by exploring the time-frequency connectedness between green bonds (GBs) and green equities. Specifically, we examine the degree of connection between GBs and green equities, the extent to which these markets influence each other, and which one is the primary net transmitter versus the net receiver of shocks under diverse market conditions. To accomplish these objectives, we use the wavelet-based Quantile-on-Quantile (QQ), dynamic conditional correlation (DCC), portfolio implications, and Quantile VAR approaches. The results show that GBs and green equities have a strong positive connection, depending on time and frequency domains. However, a negative association between GBs and green equities is observed during periods of crisis, highlighting GBs' ability to hedge green equity portfolios. The portfolio strategies demonstrate that investors require to invest in the Green Economy equity and S&P GB portfolio to reach the highest level of hedging effectiveness. The findings further imply that the Global Water Equity Index transmits the highest spillover to other green assets, while the Green Economy Equity Index receives the most spillover from other assets. The pairwise volatility connectivity reveals that most pairs have minimal quantile dependence, indicating the potential for diversification across the GB and green equity pairs. These findings have significant implications for investors and policymakers concerned with green investments and climate change mitigation.

Information ignorance refers to the act of deliberately avoiding, neglecting, or distorting information to uphold a positive self-image and protect our identity-based beliefs. We apply this framework to household finance and develop a concise 12-item questionnaire measuring individuals' receptiveness to financial information, or the lack thereof - the Financial Homo Ignorans (FHI) Scale. We conduct two studies with samples from the general population in Sweden (total N=2508) and show that the FHI scale has high reliability and distinct from other commonly used individual-difference measures in behavioral finance. We show that individual heterogeneity as assessed by the FHI scale explains a substantial variation in financial behaviors and financial well-being, also when controlling for demographics and financial literacy. These results unequivocally demonstrate the utility of the FHI scale as a valuable instrument for researchers and practitioners in comprehending and addressing the challenges posed by the omnipresence of financial information in today's world.

We investigate the event-based geopolitical shocks from the Russian invasion of Ukraine on agricultural and energy commodities using daily event-based structural vector autoregression (SVAR). We find that the geopolitical shock affects the markets of wheat (2%), corn (1%), and European natural gas (7.5%). However, substantial heterogeneity is observed among the agricultural and energy markets. Geopolitical risk stemming from the Russia-Ukraine conflict affects the European natural gas market more strongly than the US and Asian markets. The regional segment of natural gas markets could explain this. Finally, our analysis explores how geopolitical news affects the dynamics of stock, currency, and bond markets.

The stomach-derived hormone ghrelin plays not only a role in feeding, starvation, and survival, but it has been suggested to also be involved in the stress response, in neuropsychiatric conditions, and in alcohol and drug use disorders. Mechanisms related to reward processing might mediate ghrelin's broader effects on complex behaviors, as indicated by animal studies and mostly correlative human studies. Here, using a within-subject double-blind placebo-controlled design with intravenous ghrelin infusion in healthy volunteers (n = 30), we tested whether ghrelin alters sensitivity to reward and punishment in a reward learning task. Parameters were derived from a computational model of participants' task behavior. The reversal learning task with monetary rewards was performed during functional brain imaging to investigate ghrelin effects on brain signals related to reward prediction errors. Compared to placebo, ghrelin decreased punishment sensitivity (t = -2.448, p = 0.021), while reward sensitivity was unaltered (t = 0.8, p = 0.43). We furthermore found increased prediction-error related activity in the dorsal striatum during ghrelin administration (region of interest analysis: t-values >= 4.21, p-values <= 0.044). Our results support a role for ghrelin in reward processing that extends beyond food-related rewards. Reduced sensitivity to negative outcomes and increased processing of prediction errors may be beneficial for food foraging when hungry but could also relate to increased risk taking and impulsivity in the broader context of addictive behaviors.

China is promoting carbon neutrality to cope with environmental degradation and economic loss, issuing more green bonds than any other country to finance its green transformation. Uncertainty affects green bonds more than traditional bonds, including policy uncertainty, natural disasters, and energy crises. This chapter advocates green bond underlying volatility swaps, a derivative that allows investors to trade green bond price volatility, which market participants can use for hedging. We propose a framework for forecasting realized volatility by demonstrating that Chinese green bonds are highly homogeneous, making them useful in such forecasting and thus guiding trading in such swaps. We also examine the forecasting performance of a novel model, RVNET-GARCH, which synthesizes multiple green bonds’ historical realized volatility into a network factor. Testing for robustness with three Monte Carlo simulations and six rolling horizons shows that the proposed methodology can provide reliable results.

In this paper, we construct a Dynamic Stochastic General Equilibrium (DSGE) model to examine the implications of dual rates for green lending. We demonstrate that implementing a distinct interest rate for banks engaged in green lending can effectively mitigate transition risks while channeling more capital towards green production sectors and firms for an immediate cut of emissions and net zero emission economy targets.

In this commentary, we expand on the special issue themes of applied affective science, ecologically valid data and application, and the need for transdisciplinary collaboration by discussing and exemplifying how affective science can inform behavioral public policy.

We study systemic risk drivers of FinTech and traditional financial institutions under normal and extreme market conditions. We use machine learning (ML) techniques (i.e. random forest and gradient boosted regression trees) to evaluate the role of macroeconomic variables, firm characteristics, and network topologies as systemic risk drivers and perform the ML-based interpretation by Shapley individual and interaction values. We find that (i) the feature importance in driving systemic risk depends on market conditions; namely, market volatility (MVOL), individual stock volatility (IVOL), and market capitalization (MC) are positive drivers of systemic risk under extreme (downside and upside) market conditions, while under normal market conditions, institutions with high price-earnings ratio, large MC, and low IVOL play an essential role in stabilizing markets; (ii) macroeconomic variables are the most important extreme systemic risk drivers, while firm characteristics are more important under normal market conditions; and (iii) the interaction between IVOL and MC or MVOL is the significant source of extreme systemic risk, and MC is the most crucial interaction attribute under normal market conditions. The interactions between macroeconomic variables are the most prominent in systemic risk under different market conditions.

The aim of this article is twofold. First, we analyze whether the decision of where to import from is affected by firms' ex-ante characteristics. Second, we analyze how the origin of imports affects firms' productivity, export sales, and the number of export markets. Using extensive data on Swedish manufacturing firms from 2007 to 2020, we uncover several significant insights. Nearly 80% of the firms engage in international trade. The smallest firms operate exclusively as exporters, medium-sized firms as importers, and the largest firms engage in two-way trading. While most imports originate from high-wage countries, there has been a gradual shift to low-wage countries over time. Self-selection is evident, with highly productive firms importing from all sources, followed by firms that exclusively import from either low-wage or high-wage countries, and the lowest-productive firms not importing. By controlling for self-selection using the Event Study approach and difference-in-differences matching estimator, we find that large importing firms exhibit no significant differences in productivity and export sales in comparison to their non-importing counterparts. However, small importing firms show increased productivity growth, driven by high-wage imports. Both small and large firms importing from high- and low-wage countries tend to access more high-wage export markets than non-importers.

We analyse time-varying risk spillover and dependence to assess the systemic risk benefits of ethical, sustainable, and green investments. Our data comprise sustainable investments from ethical, environmental, social and governance (ESG), and green bonds. We investigate the link to major asset classes, including equity, commodity, and currency markets. We find evidence of close connection between the major asset classes and sustainable assets, except green bonds. We also explore the improvement in hedging efficiency from combining ethical and ESG investments with commodities and currencies over investment horizons. Our analysis based on systemic risk measures indicates that there is evidence of lower time-scale systemic risk connectedness in the case of commodities and currencies combined with ethical and ESG assets. These findings have significant implications for portfolio managers, policymakers, and market participants.

We estimate the income and fuel price elasticities of private car vehicle kilometres travelled (VKT) using fixed effects on registry micro panel data covering all Swedish households from 1999 to 2018. Such registry data, covering all individuals and cars in the country, are unique to Nordic countries and are comprehensive enough to allow fine segmentation of the population by both income groups and several municipality types. To address potential endogeneity arising if employees receive a wage compensation for long commutes, we apply the temporal changes in earned income tax credits as an instrumental variable. We find lower income and price elasticities (in absolute value) in the large cities, and larger elasticities in suburbs, other cities and in rural areas. We also find that the elasticities decrease with income, excluding the lowest income quartile, having the lowest elasticities. Specifically, we show theoretically and empirically that because the income elasticity varies considerably along the income distribution, the resulting income elasticity depends heavily on how the estimator assigns weight to different income groups, unless the specification explicitly allows for variation in the impact of income on VKT. Moreover, the impact of an income increase depends on to whom the income increase accrues to. For a uniform income increase, 0.2 is the preferred income elasticity. Our preferred long-run fuel price elasticity is -0.53. The short-run elasticities are lower. These elasticities apply to the full population and not only to car owners or drivers.

This study examines the interconnectedness and risk profile of hydrogen in comparison to other assets from December 2019 to April 2022, using a time-varying copula approach. The findings reveal that hydrogen's relationships with conventional commodities and markets can shift significantly during extreme uncertainty. The COVID-19 pandemic had a marked impact on hydrogen's market connections. However, hydrogen did not uniformly increase linkages, highlighting its distinct profile even as an energy commodity. Despite its sensitivity to crises, hydrogen's reactions were varied, emphasizing the necessity for customized interpretations. Calculation of value-at-risk, conditional value-at-risk and Delta CoVaR demonstrated that green bonds exhibited the lowest investment risks across frequencies, which can be attributed to factors such as government support and growing demand. In the case of hydrogen, the risk metrics were inconsistent, reflecting its status as an early-stage adoption asset with niche applications in transportation and industry. These findings have key implications for managing risk associated with energy transition and for facilitating the adoption of hydrogen. The empirical insights provided herein can aid policymakers in developing supportive regulations and incentives to expedite the scaling of hydrogen. Moreover, Investors can leverage hydrogen's risk quantification for portfolio optimization and hedging strategies. Overall, by elucidating hydrogen's unique dynamics, this study informs stakeholder decisions to facilitate the hydrogen economy.

Research on intertemporal and prosocial decisions has largely developed in separate strands of literature. However, many of the decisions we make occur at the intersection of these two dimensions (intertemporal and prosocial). Trust is an example, where a decision today is made with the expectation that another person will reciprocate (or betray) later. A new literature is emerging to explore the role of time in these types of situations, where time and social considerations are intertwined. In many cases, time introduces (or magnifies) an element of uncertainty about future outcomes and utility that people need to deal with - what will happen, how good will it be, how will it feel. We review this emerging literature on intertemporal prosocial decision-making and discuss how new research can fill existing knowledge gaps.

We study optimal degree of bus system electrification for Stockholm's longest high-frequency bus line. We evaluate the welfare effects of opportunity and depot charging fleet configurations with batteries charged during dwell times at terminal stations or during the operating pause in the bus depot, respectively. Electric buses (e-buses) significantly reduce carbon and health damaging emissions of transit services. However, e-buses are presently not welfare improving, because their lower external costs do not offset the higher supply costs (e.g., capital cost of charging infrastructures and batteries). Instead, we find that optimising bus fares and frequencies and road pricing is more effective in improving social welfare and carbon emissions. E-buses significantly reduce surplus of bus operators, which thus are reluctant to adopt these technologies without direct public support. Sensitivity analysis shows that: (i) technological developments to substantially reduce capital costs can make e-buses perform well from a social welfare perspective; (ii) efficiency gains obtained in the operation of the service, e.g., by optimizing on-board conditioning systems, but also bus routing and driving style, can have a greater impact on the cost performance of e-bus fleet configurations than simply reducing capital costs. An argument for ebuses is the efforts in coordinating a transition to electrified vehicles, aiming at reducing the risk of futile investments in charging infrastructure.

The urgent shift towards a zero- or low-carbon economy to combat climate change has heightened interest in green financial instruments among investors. Although green financial assets have grown significantly in a decade, investing in green assets is speculated to be costlier than traditional assets. Against this backdrop, we analyse whether investing in green financial assets is costlier than investing in traditional assets. We employ a comprehensive methodology, encompassing risk-adjusted returns, tail risks, time-varying correlations, novel quantile volatility connectedness, and portfolio implication techniques to show that most green assets outperform non-green assets in terms of risk-adjusted returns. Likewise, the potential loss likelihood of investing in green assets is lower. Our time-varying correlation outcomes reveal a strong positive association between green assets and their traditional counterparts, with limited hedging opportunities. Further, quantile vector autoregression results suggest that total connectedness between the green assets and their non-green pairs is lower in the normal market than in the extreme markets. Green and non-green asset pairs are also reciprocal in spreading and absorbing volatility shocks across most market states. Finally, the portfolio implications reveal that most asset pairs have a higher hedging cost; however, allocating more than 90% of funds to green assets can provide significant hedging effectiveness. Overall, investing in green assets is not costlier than investing in non-green assets, but they may be marginally rewarded. Our empirical findings have crucial implications for investors, policymakers, and regulatory bodies.

Our study aims to investigate the seasonal patterns of returns and evaluate the effects that various factors have on the performance in a large data set (125 funds) of Islamic mutual funds from four regions: Asia-Pacific, North America, Europe, and the Middle East and North Africa (MENA). We employed indicators for consumer sentiment, economic policy uncertainty, implied stock market volatility, the trade-weighted US dollar, the Carhart (1997) risk factors, and idiosyncratic risk. Our findings indicate that the seasonal patterns and determinants of Islamic mutual funds' financial performance tend to differ significantly across the regions. This may be explained by the different cultural/religious settings, the different backgrounds of the market participants as well as differences in the holiday seasons and end of fiscal year/taxation across regions/countries. Global fund managers and investors may benefit from the obtained results when constructing portfolios and designing hedging strategies.

One important factor that hampers children's learning of mathematics is math anxiety (MA). Still, the mechanisms by which MA affects performance remain debated. The current study investigated the relationship between MA, basic number processing abilities (i.e., cardinality and ordinality processing), and executive functions in school children enrolled in grades 4-7 (N = 127). Children were divided into a high math anxiety group (N = 29) and a low math anxiety group (N = 31) based on the lowest quartile and the highest quartile. Using a series of analyses of variances, we find that highly math-anxious students do not perform worse on cardinality processing tasks (i.e., digit comparison and non-symbolic number sense), but that they perform worse on numerical and non-numerical ordinality processing tasks. We demonstrate that children with high MA show poorer performance on a specific aspect of executive functions-shifting ability. Our models indicate that shifting ability is tied to performance on both the numerical and non-numerical ordinality processing tasks. A central factor seems to be the involvement of executive processes during ordinality judgements, and executive functions may constitute the driving force behind these delays in numerical competence in math-anxious children.

In shared decision-making (SDM), the role of emotions and information avoidance is crucial yet often overlooked. We highlight three key aspects of how emotions impact medical decision-making that physicians must understand and utilize for SDM to effectively contribute to sense-making: (i) prominence thinking, (ii) risk as feeling versus risk as analysis, and (iii) preferences for more versus less healthcare. We introduce the novel concept of affective paternalism as a tool for physicians to help patients navigate their emotions by providing not only factual information but also emotional support and guidance. This approach involves recognizing and addressing patients' fears, hopes, and anxieties, thereby helping them process information more comprehensively. By acknowledging and addressing the emotional components inherent in medical decisions, affective paternalism helps patients make more informed and balanced choices, aligning treatment decisions with their overall well-being.

Are people more likely to (mis)interpret information so that it aligns with their ideological identity when relying on feelings compared to when engaging in analytical thinking? Or is it the other way around: Does deliberation increase the propensity to (mis)interpret information to confirm existing political views? In a behavioral experiment, participants (n = 1207, Swedish sample) assessed numerical information concerning the effects of gender quotas and immigration either under time pressure or under no time pressure. To measure trait differences in cognitive sophistication, we also collected data on numeric ability. We found clear evidence of motivated reasoning when assessing both the effects of gender quotas on companies’ financial results and the effect of refugee intake on crime rates. Subjects who prioritized equality over liberty on the labor market were 13 percentage points less likely to correctly assess numerical information depicting that companies that used gender quotas when hiring made less profit. Subjects who classified themselves as ‘Swedes’ rather than ‘World citizens’ were 14 percentage points less likely to correctly assess numerical information depicting that crime rates decreased following immigration. Time pressure did not affect the likelihood to engage in motivated reasoning, while subjects with higher numeric ability were less likely to engage in motivated reasoning when analyzing information concerning refugee intake, but more likely to engage in motivated reasoning when analyzing information regarding the effect of gender quotas. Together these results indicate that motivated reasoning is primarily driven by individual differences in analytical thinking at the trait level and not by situational factors such as time pressure, and that whether motivated reasoning is primarily driven by analysis or feelings depends on the topic at hand.

This study investigates the interconnectedness of ASEAN-4, regional, and global financial markets by analyzing risk spillover layers using multilayer information spillover network topology across instruments including bonds, forex, and stocks. The findings uncover intricate relationships between markets. Extreme risk and volatility spillover layers may indicate early financial crises, while mean spillovers exhibit hysteresis, peaking during or after crises. ASEAN-4 interconnectedness remains relatively stable, while global markets demonstrate robust interconnectedness with high overlap. The findings improve understanding of global financial structure amid deglobalization, holding policymaker and participant implications by revealing complex connections during financial crises.

We construct correlation-based networks linking 86 assets (stock indices, bond indices, foreign exchange rates, commodity futures, and cryptocurrencies) and analyze the impact of asset selection on portfolio optimization using different centrality measures (including degree, eigenvector, eccentricity, betweenness, PageRank, and hybrid centralities). In times of a global crisis, peripheral assets located in cross-market networks are more suitable for investment. By comparing portfolio performance based on different centrality measures, we find that (i) hybrid, eigenvector, and PageRank centralities can best improve portfolio performance; (ii) degree centrality is suitable for larger portfolios; and (iii) eccentricity and betweenness centralities are unsuitable for network optimization portfolios. In response, we explain them based on the construction principle of centrality measures. Additionally, our optimal portfolios suggest that investors pay more attention to the role of emerging countries, which are less exposed to external shocks and whose financial markets are more likely to remain stable. (c) 2024 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This paper examines quantile coherency in bonds, commodities, currencies, and equities using a novel quantile coherency approach. While recent literature has explored single-frequency tail and time-frequency dependence in asset returns, we provide fresh evidence on asset return dependence across quantiles (proxying business cycles or market conditions) at different frequencies (representing investment horizons). Considering sixty-seven individual asset return series in four asset classes, we observe that low frequency (yearly) dependence is stronger in the bond, foreign exchange, and equity markets. Specifically, we find strong dependence between the German and French bond markets, heating oil and crude oil, gold and silver, British Pound, and Euro, French and German and Canadian and US equities. As we report asset return interdependence in different business cycles and at different time horizons, these results have important implications for portfolio allocation and investment strategy formulation.

The global financial crisis has brought increased attention to the consequences of international reserves holdings. In an era of high financial integration, we investigate the relationship between the real exchange rate and international reserves using nonlinear regressions and panel threshold regressions over 110 countries from 2001 to 2020. Our study shows the level of financialinstitution development plays an essential role in explaining the buffer effect of international reserves. Countries with a low development of their financial institutions may manage the international reserves as a shield to deal with the negative consequences of terms-of-trade shocks on the real exchange rate. We also find the buffer effect is stronger in countries with intermediate levels of financial openness.

This article uses the interacted panel VAR method to analyse how institutional factors related to the structure of the housing market explain cross-country heterogeneity in responses to macroeconomic shocks. While the previous literature focused on the stabilizing role of the mortgage market, we argue that housing tenure structure also plays an important role. In the baseline, we use data for nine OECD members to investigate how the size and regulations of the rental market affect the response of the housing market to interest rate shocks. As a reference, we also conduct a similar analysis with the mortgage market structure as the institutional factor. We find that both the rental market size and maximum loan-to-value ratios are important in explaining heterogeneity of housing market responses to macroeconomic shocks.

This study examines the effect of making judgments in public (vs. private) on the moral permissibility and willingness to engage in three types of potentially repugnant markets (organ sale, prostitution, marijuana). An experiment was conducted where participants responded to a series of questions about repugnant markets and their answers were either publicly revealed to the group they were in, using their name and photo, or kept fully anonymous. There was no effect of making judgments in public for markets for organs or drugs. For prostitution, however, subjects judged it as substantially less permissible and reported lower willingness to engage in the activity (assuming it was legal) when asked in public compared to when asked anonymously. These effects were mainly driven by male participants. Our study confirms that social signaling plays an important role when understanding when and why people judge certain markets as morally (un)permissable.

This study investigates the volatility dynamics of oil and gas prices in an environment characterized by postcoronavirus disease 2019 recovery, uncertainty, high inflation, and geopolitical tensions. Unlike previous studies, we examine a long-run series of high-frequency data on gas and oil prices from July 2007 to May 2022, which provides more than one million observations with which to analyze volatility. We compute realized volatility (RV) and decompose it into continuous volatility and jumps. We then investigate the relationship between uncertainty, investor sentiment, and RV, as well as its main components. Econometrically, we extend the heterogeneous autoregressive model of Corsi (2009) while considering not only disaggregate proxies for volatility (jumps and continuous volatility) and introducing uncertainty and heterogeneous investor sentiment, but also by allowing the model to include asymmetry, nonlinearity, and time variation according to the regime under consideration. Our results present three main findings. First, we find significant evidence of volatility decomposition, suggesting that both markets are characterized by significant jumps. Second, we show that trading volume, extra-financial news (uncertainty, investor sentiment), and jumps appear to drive commodity price volatility. Third, we find evidence of nonlinearity and threshold effects on energy price volatility. These findings are relevant for policymakers, regulators, investors, and portfolio managers, as they enable them to better characterize and forecast changes in commodity prices.

We investigate the degree of digitalization required to gain a competitive advantage in the supply chain by developing a firm-specific metric based on firm disclosure. Using a 2011 -2020 sample of Chinese listed firms, we examine whether improving corporate digitalization can bring more trade credit financing from the supply chain. Our findings indicate that firms acquire more trade credit after increasing their level of digitalization, despite the low pressure of credit rationing. Furthermore, digitalization improves operation, research and development, and governance efficiency, giving such firms a competitive advantage. Cross-sectional analyses indicate that specific characteristics, such as a large firm size, state-owned property, traditional industry type, stable macropolicy environment, high industry status, and transparent internal information environment, can bolster this competitive advantage. In general, we highlight the role of digitalization in improving firms ' competitiveness in the supply chain from the perspective of trade credit financing.

The banking sectors in the Scandinavian countries are highly concentrated, typically undercapitalised and they have suffered through several crises since the 1990s. This article analyses the systemic risk in Denmark, Norway and Sweden focusing on the co-dependence in the tails of equity returns of an individual bank and the overall banking system. We use, partly in a new way, conditional cross-quantilograms (CQs) for this purpose. We find that the CQs are positive and statistically significant in the low and high quantiles indicating that the Scandinavian banks are systemically linked. The low-quantile dependence is relatively stronger compared with the magnitude of dependence in the other quantiles. These results hold even after controlling for equity market volatility and economic policy uncertainty. We further observe that the systemic risk was insignificant from the early-2000 to the outbreak of the global financial crisis (GFC). However, after the GFC and the euro zone crisis, the systemic risk has increased substantially. Finally, we find that bank size has a positive relationship with systemic risk (low-quantile dependence) while return on asset and loan to deposit ratio exhibit a negative influence. Furthermore, these relationships are asymmetric across quantiles.

Based upon generalized spillover index method under Markov switching vector auto-regression (MS-VAR) framework, this paper aims at a regime dependent measure of the volatility spillover asymmetry across Shanghai, Hong Kong and the U.S. stock markets. For that, we apply a regime weighted measure of spillover and its asymmetry. The empirical results show that there existed evident negative asymmetric effect of spillover across the three markets, and it was regime dependent and time-varying: it got intensified under high volatility regime and turned out stronger after the Program of Shanghai-Hong Kong stock connect. The regime weighted measure of spillover asymmetry is found to be reliable; it could be explained appropriately with the economic policy uncertainty and investors fear in the U.S., extreme shocks like crash of Shanghai stock market and COVID-19 as well as the capital flow through the Program. From in-sample evidence and out-of-sample forecast of Shanghai stock market, we infer that traditional forecast models could be improved if regime dependent spillover and its asymmetry are considered as additional factors.

We conducted two studies investigating how financial well-being was affected by the COVID-19 outbreak. Across both studies conducted in Sweden, we find that COVID-19 was associated with an overall improvement in subjective financial well-being. The positive effect was driven by a general decline in anxiety toward current financial matters, while financial security with regard to the future declined (Study 1) or was unaffected (Study 2). These results might seem paradoxical. But we propose two explanations: (a) People have a limited ability to worry about two things at the same time. Financial problems might therefore be less emotionally salient in the face of more urgent nonfinancial problems and (b) Some people likely experienced an initial slack in their household finances due to decreased spending opportunities at the onset of COVID-19, which to some extent could counteract increased worry about future financial security.