Pub Date : 2025-09-01Epub Date: 2025-07-23DOI: 10.1016/j.najef.2025.102508
Lucio Gobbi , Ronny Mazzocchi , Roberto Tamborini
When inflation picks up, central banks fear that de-anchored expectations trigger ever increasing inflation, but this scenario does not materialize in the standard New Keynesian (NK) blueprint for central banks. Divergent inflation processes may result introducing boundedly rational beliefs about future inflation that de-anchor endogenously, together with indexed wages and persistent shocks. However, by means of simulations of the model, we find that the relevant parameters should be far beyond their consensus empirical values. Either the concern with the de-anchoring of inflation expectations is overrated or it should be given different theoretical underpinnings than the NK ones.
{"title":"Inflation shocks and the New Keynesian model: When should central banks fear inflation expectations?","authors":"Lucio Gobbi , Ronny Mazzocchi , Roberto Tamborini","doi":"10.1016/j.najef.2025.102508","DOIUrl":"10.1016/j.najef.2025.102508","url":null,"abstract":"<div><div>When inflation picks up, central banks fear that de-anchored expectations trigger ever increasing inflation, but this scenario does not materialize in the standard New Keynesian (NK) blueprint for central banks. Divergent inflation processes may result introducing boundedly rational beliefs about future inflation that de-anchor endogenously, together with indexed wages and persistent shocks. However, by means of simulations of the model, we find that the relevant parameters should be far beyond their consensus empirical values. Either the concern with the de-anchoring of inflation expectations is overrated or it should be given different theoretical underpinnings than the NK ones.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102508"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the systemic risk spillover from various oil price shocks (demand, supply, and risk) to several green investments covering sustainable, ESG, clean technology, carbon market, clean energy, and green bonds and assesses the hedging and safe-haven roles of these green investments against oil shocks. Based on daily data from January 4, 2012 to September 20, 2022, oil prices are decomposed and a dynamic conditional correlation model is used to assess conditional value-at-risk (CoVaR) as a measure of upper risk spillover from each oil price shock to green investments. The hedging and safe-haven roles of the green investments are examined, especially during the COVID-19 pandemic and Russia-Ukraine conflict. The results show that all upper CoVaRs resulting from oil demand shocks exceed the investment’s upper tail VaRs during Phase 1 of COVID-19, indicating a significant oil demand shock risk spillover to all green investments. During Phase 2 of COVID-19 and the Russia-Ukraine conflict, only some investments are influenced by demand oil shocks. When oil supply and risk shocks rise, the upside risk of all green investments tends to be mitigated, suggesting that, during unstable periods, investors should seek green investments to mitigate the risk spillovers of these two oil shocks. Further analysis indicates that the majority of green investments serve as diversifiers for oil demand shocks, and act as hedges against oil supply and risk shocks. However, only a few of these green investments are strong safe havens.
{"title":"Oil price shocks and green investments: Upside risks, hedging, and safe-haven properties","authors":"Nedal Al-Fayoumi , Bana Abuzayed , Elie Bouri , Nadia Arfaoui","doi":"10.1016/j.najef.2025.102502","DOIUrl":"10.1016/j.najef.2025.102502","url":null,"abstract":"<div><div>This study investigates the systemic risk spillover from various oil price shocks (demand, supply, and risk) to several green investments covering sustainable, ESG, clean technology, carbon market, clean energy, and green bonds and assesses the hedging and safe-haven roles of these green investments against oil shocks. Based on daily data from January 4, 2012 to September 20, 2022, oil prices are decomposed and a dynamic conditional correlation model is used to assess conditional value-at-risk (CoVaR) as a measure of upper risk spillover from each oil price shock to green investments. The hedging and safe-haven roles of the green investments are examined, especially during the COVID-19 pandemic and Russia-Ukraine conflict. The results show that all upper CoVaRs resulting from oil demand shocks exceed the investment’s upper tail VaRs during Phase 1 of COVID-19, indicating a significant oil demand shock risk spillover to all green investments. During Phase 2 of COVID-19 and the Russia-Ukraine conflict, only some investments are influenced by demand oil shocks. When oil supply and risk shocks rise, the upside risk of all green investments tends to be mitigated, suggesting that, during unstable periods, investors should seek green investments to mitigate the risk spillovers of these two oil shocks. Further analysis indicates that the majority of green investments serve as diversifiers for oil demand shocks, and act as hedges against oil supply and risk shocks. However, only a few of these green investments are strong safe havens.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102502"},"PeriodicalIF":3.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-06-15DOI: 10.1016/j.najef.2025.102488
Jan Muckenhaupt , Martin Hoesli , Bing Zhu
Assets’ capability to hedge against inflation has again come to the forefront given the recent surge in inflation. This paper investigates the inflation-hedging capability of an important asset class, i.e., real estate, using data from 1990 to the end of 2023 across six countries. By using a Panel Markov switching vector error correction model (MS-VECM), we identify the hedging ability of real estate in crisis and non-crisis periods, both in the short and long term. Real estate provides an effective hedge against inflation in the long run, both in crisis and non-crisis periods. In the short term, real estate securities only hedge against inflation in stable periods, but direct real estate also shows desirable inflation hedging in crisis periods. Real estate (both direct and securitized) effectively serves as a hedge against inflation shocks, particularly protecting against unexpected inflation and against energy inflation during stable periods. While stocks surpass real estate (both direct and securitized) in long-term inflation protection and real estate has short-term benefits, gold distinguishes itself by offering reliable long-run protection, but only in economic downturns. The results should provide important insights to investors seeking to allocate resources more efficiently in those turbulent times, both over the short and long term.
{"title":"Real estate as an inflation hedge: new evidence from an international analysis","authors":"Jan Muckenhaupt , Martin Hoesli , Bing Zhu","doi":"10.1016/j.najef.2025.102488","DOIUrl":"10.1016/j.najef.2025.102488","url":null,"abstract":"<div><div>Assets’ capability to hedge against inflation has again come to the forefront given the recent surge in inflation. This paper investigates the inflation-hedging capability of an important asset class, i.e., real estate, using data from 1990 to the end of 2023 across six countries. By using a Panel Markov switching vector error correction model (MS-VECM), we identify the hedging ability of real estate in crisis and non-crisis periods, both in the short and long term. Real estate provides an effective hedge against inflation in the long run, both in crisis and non-crisis periods. In the short term, real estate securities only hedge against inflation in stable periods, but direct real estate also shows desirable inflation hedging in crisis periods. Real estate (both direct and securitized) effectively serves as a hedge against inflation shocks, particularly protecting against unexpected inflation and against energy inflation during stable periods. While stocks surpass real estate (both direct and securitized) in long-term inflation protection and real estate has short-term benefits, gold distinguishes itself by offering reliable long-run protection, but only in economic downturns. The results should provide important insights to investors seeking to allocate resources more efficiently in those turbulent times, both over the short and long term.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102488"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-17DOI: 10.1016/j.najef.2025.102501
Ronghua Luo , Zeyu Huang , Yangyi Liu
We introduce the Relative Downside Tracking Error (RDTE) model, a dynamic enhanced indexing method that adapts to the time-varying and mean-reverting nature of market volatility. The RDTE model dynamically adjusts the weights assigned to downside deviations based on market volatility, allowing for greater flexibility during high-volatility periods. This flexibility helps the model reduce the emphasis on short-term fluctuations, focusing instead on minimizing overall downside risk. By doing so, the model effectively controls portfolio distortion, leading to more stable long-term performance. Empirical analyses of U.S. and Chinese stock markets demonstrate that the RDTE model consistently outperforms traditional models, delivering higher returns, lower downside risk, and better risk-adjusted performance. This outperformance is driven by the RDTE model’s effective downside risk management during volatile periods, as confirmed by its superior long-term performance in both markets.
{"title":"Enhanced index tracking: A relative downside risk approach","authors":"Ronghua Luo , Zeyu Huang , Yangyi Liu","doi":"10.1016/j.najef.2025.102501","DOIUrl":"10.1016/j.najef.2025.102501","url":null,"abstract":"<div><div>We introduce the Relative Downside Tracking Error (RDTE) model, a dynamic enhanced indexing method that adapts to the time-varying and mean-reverting nature of market volatility. The RDTE model dynamically adjusts the weights assigned to downside deviations based on market volatility, allowing for greater flexibility during high-volatility periods. This flexibility helps the model reduce the emphasis on short-term fluctuations, focusing instead on minimizing overall downside risk. By doing so, the model effectively controls portfolio distortion, leading to more stable long-term performance. Empirical analyses of U.S. and Chinese stock markets demonstrate that the RDTE model consistently outperforms traditional models, delivering higher returns, lower downside risk, and better risk-adjusted performance. This outperformance is driven by the RDTE model’s effective downside risk management during volatile periods, as confirmed by its superior long-term performance in both markets.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102501"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
By analyzing an association between return dispersions and market returns in cryptocurrency markets, geopolitical risk (GPR) stimulates herding at the market-wide level. We augment the aggregate herding detection models of Chang, Cheng, and Khorana (2000) and find that severe herd behavior is presented in nearly all cases. Thus, the GPR is an essential moderating factor to promote herd behavior in crypto assets. Considering the GPR sub-indices, the GPR Threat index has a stronger impact than the GPR Act index. Imitating trades are more prevalent during bearish markets, confirming asymmetric herd behavior. Specifically, herd behavior is the strongest during the COVID-19 pandemic and the Russia-Ukraine war. We infer that herding is intentional, as information symmetry, disclosure, and quality in cryptocurrency markets are relatively low. Overall findings support the “fear of missing out” (FOMO) phenomenon and the pump and dump schemes suggested by Baur and Dimpfl (2018).
{"title":"Geopolitical risk, herd behavior, and cryptocurrency market","authors":"Phasin Wanidwaranan , Jutamas Wongkantarakorn , Chaiyuth Padungsaksawasdi","doi":"10.1016/j.najef.2025.102487","DOIUrl":"10.1016/j.najef.2025.102487","url":null,"abstract":"<div><div>By analyzing an association between return dispersions and market returns in cryptocurrency markets, geopolitical risk (GPR) stimulates herding at the market-wide level. We augment the aggregate herding detection models of Chang, Cheng, and Khorana (2000) and find that severe herd behavior is presented in nearly all cases. Thus, the GPR is an essential moderating factor to promote herd behavior in crypto assets. Considering the GPR sub-indices, the GPR Threat index has a stronger impact than the GPR Act index. Imitating trades are more prevalent during bearish markets, confirming asymmetric herd behavior. Specifically, herd behavior is the strongest during the COVID-19 pandemic and the Russia-Ukraine war. We infer that herding is intentional, as information symmetry, disclosure, and quality in cryptocurrency markets are relatively low. Overall findings support the “fear of missing out” (FOMO) phenomenon and the pump and dump schemes suggested by Baur and Dimpfl (2018).</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102487"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-30DOI: 10.1016/j.najef.2025.102516
Feipeng Zhang , Yuhan Ma , Xu Liu , Xiaoying Zhou
This paper provides a comprehensive reassessment of gold’s role as a safe haven, hedge, and portfolio diversifier across the stock markets of G7 and E7 countries from January 1, 2000, to December 31, 2024. We employ an integrated empirical framework, combining quantile-on-quantile (QQ) regression, causality-in-quantiles testing, and the cross-quantilogram method. This approach allows us to capture asymmetric and heterogeneous dependencies across the joint distribution of gold and stock returns. The findings reveal that gold acts as a safe haven during market downturns in most G7 countries, particularly where gold comprises a large share of official reserves. In contrast, gold typically serves as a diversifier in E7 countries. However, under specific asymmetric market conditions, gold exhibits hedging or safe-haven behavior in some E7 countries, such as Turkey, India, and Brazil. The results also highlight the role of gold reserve composition in enhancing gold’s safe-haven properties. In countries with substantial official gold holdings, gold demonstrates more robust safe-haven capabilities. The causality-in-quantiles analysis further confirms bidirectional and nonlinear predictive relationships across quantiles, while recursive and sub-sample QQ estimations indicate that the safe-haven function of gold is time-varying and evolves in response to systemic shocks. These findings provide valuable insights for both investors and policymakers by highlighting the varying effectiveness of gold as a risk management instrument across various markets and economic conditions, emphasizing the importance of tailored strategies in uncertain financial environments.
{"title":"Revisiting the hedging and safe haven roles of gold: Evidence from quantile-on-quantile approach","authors":"Feipeng Zhang , Yuhan Ma , Xu Liu , Xiaoying Zhou","doi":"10.1016/j.najef.2025.102516","DOIUrl":"10.1016/j.najef.2025.102516","url":null,"abstract":"<div><div>This paper provides a comprehensive reassessment of gold’s role as a safe haven, hedge, and portfolio diversifier across the stock markets of G7 and E7 countries from January 1, 2000, to December 31, 2024. We employ an integrated empirical framework, combining quantile-on-quantile (QQ) regression, causality-in-quantiles testing, and the cross-quantilogram method. This approach allows us to capture asymmetric and heterogeneous dependencies across the joint distribution of gold and stock returns. The findings reveal that gold acts as a safe haven during market downturns in most G7 countries, particularly where gold comprises a large share of official reserves. In contrast, gold typically serves as a diversifier in E7 countries. However, under specific asymmetric market conditions, gold exhibits hedging or safe-haven behavior in some E7 countries, such as Turkey, India, and Brazil. The results also highlight the role of gold reserve composition in enhancing gold’s safe-haven properties. In countries with substantial official gold holdings, gold demonstrates more robust safe-haven capabilities. The causality-in-quantiles analysis further confirms bidirectional and nonlinear predictive relationships across quantiles, while recursive and sub-sample QQ estimations indicate that the safe-haven function of gold is time-varying and evolves in response to systemic shocks. These findings provide valuable insights for both investors and policymakers by highlighting the varying effectiveness of gold as a risk management instrument across various markets and economic conditions, emphasizing the importance of tailored strategies in uncertain financial environments.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102516"},"PeriodicalIF":3.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144772434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using data on hourly frequency observed temperature and daily forecasted temperatures across major U.S. metropolitan areas over a 30-year period, we analyze the relationship between the daily returns of the NYMEX Henry Hub Natural Gas futures and U.S. weather fluctuations. We propose the existence of a novel risk premium linked to extreme weather forecasts for U.S. Natural Gas futures, which outperforms the S&P500 index on an absolute and risk-adjusted basis over a 30-year period. Our findings contribute to opening a new perspective on the non-linear interplay between weather and financial markets emphasizing the importance of these factors in financial risk management and in the context of climate change.
{"title":"Can extreme weather forecasts lead to a risk premium? Evidence of a non-linear response in U.S. natural gas futures","authors":"Manou Monteux , Maria Cristina Arcuri , Gino Gandolfi , Stefano Caselli","doi":"10.1016/j.najef.2025.102494","DOIUrl":"10.1016/j.najef.2025.102494","url":null,"abstract":"<div><div>Using data on hourly frequency observed temperature and daily forecasted temperatures across major U.S. metropolitan areas over a 30-year period, we analyze the relationship between the daily returns of the NYMEX Henry Hub Natural Gas futures and U.S. weather fluctuations. We propose the existence of a novel risk premium linked to extreme weather forecasts for U.S. Natural Gas futures, which outperforms the S&P500 index on an absolute and risk-adjusted basis over a 30-year period. Our findings contribute to opening a new perspective on the non-linear interplay between weather and financial markets emphasizing the importance of these factors in financial risk management and in the context of climate change.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102494"},"PeriodicalIF":3.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-08DOI: 10.1016/j.najef.2025.102497
David Y. Aharon , Shoaib Ali , Muhammad Naveed
This paper investigates the return spillover and connectedness between Artificial Intelligence (AI) and Internet of Things (IoT) tokens using the Quantile Vector Autoregression (QVAR) and quantile frequency connectedness approach. Using daily data from February 2021 to March 2024 for ten leading AI and IoT tokens, we find that connectedness is both time-varying and asymmetric across quantiles. In the short term, the Total Connectedness Index (TCI) peaks at 69.58 % under extreme market conditions (τ = 0.05), compared to 64.16 % in bull markets (τ = 0.95) and 61.43 % under normal conditions (τ = 0.50). Connectedness is weaker in the medium and long terms, but asymmetry persists as the TCI reaches 10.98 % vs. 5.32 % (medium term) and 10.52 % vs. 2.64 % (long term) for extreme vs. normal quantiles. These findings confirm that return transmission intensifies during periods of elevated market uncertainty, particularly in the left tail of the distribution. Moreover, AI and IOT tokens offer both diversification and hedging benefits against each other. Our analysis provides insights for investors, portfolio managers, and policymakers in understanding systemic risk and optimizing digital asset portfolios.
{"title":"Who A(m) I? exploring quantile frequency connectedness in emerging AI and IoT token markets","authors":"David Y. Aharon , Shoaib Ali , Muhammad Naveed","doi":"10.1016/j.najef.2025.102497","DOIUrl":"10.1016/j.najef.2025.102497","url":null,"abstract":"<div><div>This paper investigates the return spillover and connectedness between Artificial Intelligence (AI) and Internet of Things (IoT) tokens using the Quantile Vector Autoregression (QVAR) and quantile frequency connectedness approach. Using daily data from February 2021 to March 2024 for ten leading AI and IoT tokens, we find that connectedness is both time-varying and asymmetric across quantiles. In the short term, the Total Connectedness Index (TCI) peaks at 69.58 % under extreme market conditions (τ = 0.05), compared to 64.16 % in bull markets (τ = 0.95) and 61.43 % under normal conditions (τ = 0.50). Connectedness is weaker in the medium and long terms, but asymmetry persists as the TCI reaches 10.98 % vs. 5.32 % (medium term) and 10.52 % vs. 2.64 % (long term) for extreme vs. normal quantiles. These findings confirm that return transmission intensifies during periods of elevated market uncertainty, particularly in the left tail of the distribution. Moreover, AI and IOT tokens offer both diversification and hedging benefits against each other. Our analysis provides insights for investors, portfolio managers, and policymakers in understanding systemic risk and optimizing digital asset portfolios.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102497"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-06-18DOI: 10.1016/j.najef.2025.102491
Huang Wenyan
This study investigates the underexplored relationship between stock market participation and household happiness by analyzing microdata from the China Household Finance Survey (CHFS 2013, 2015, 2017). Our findings reveal a robust inverted U-shaped relationship between happiness and stock market participation, offering novel resolutions to three persistent puzzles in behavioral finance: the stock market participation puzzle, the happiness-income paradox, and the interplay between happiness and risk. Mechanism analysis further uncovers the multidimensional moderating role of risk through perceived risk, risk identification (social interaction, financial interest, and financial literacy), and background risk (urban–rural disparities and health status). The perceived risk significantly moderates the relationship between happiness and stock market participation. Risk identification factors operate distinctively with social interaction, amplify participation for moderately happy households, financial interest modulates participation nonlinearly, and financial literacy affects portfolio diversification. Background risks moderate the relationship between happiness and participation decisions and depth. These results provide critical empirical foundations for designing targeted financial policies that address heterogeneity in household risk dynamics and psychological well-being.
{"title":"Happiness and stock market participation","authors":"Huang Wenyan","doi":"10.1016/j.najef.2025.102491","DOIUrl":"10.1016/j.najef.2025.102491","url":null,"abstract":"<div><div>This study investigates the underexplored relationship between stock market participation and household happiness by analyzing microdata from the China Household Finance Survey (CHFS 2013, 2015, 2017). Our findings reveal a robust inverted U-shaped relationship between happiness and stock market participation, offering novel resolutions to three persistent puzzles in behavioral finance: the stock market participation puzzle, the happiness-income paradox, and the interplay between happiness and risk. Mechanism analysis further uncovers the multidimensional moderating role of risk through perceived risk, risk identification (social interaction, financial interest, and financial literacy), and background risk (urban–rural disparities and health status). The perceived risk significantly moderates the relationship between happiness and stock market participation. Risk identification factors operate distinctively with social interaction, amplify participation for moderately happy households, financial interest modulates participation nonlinearly, and financial literacy affects portfolio diversification. Background risks moderate the relationship between happiness and participation decisions and depth. These results provide critical empirical foundations for designing targeted financial policies that address heterogeneity in household risk dynamics and psychological well-being.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102491"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-08-08DOI: 10.1016/j.najef.2025.102519
M. Jahangir Alam
This paper examines the effect of monetary policy shocks on the Total Factor Productivity (TFP) of high-tech versus low-tech firms, focusing on how changes in borrowing costs and credit availability influence productivity. To isolate the causal effect, I use firm-level longitudinal data from Compustat’s publicly listed firms and apply the Local Projections-Instrumental Variables (LP-IV) approach, with high-frequency interest rate surprises serving as instrumental variables. The results indicate that smaller, younger, and low-cash-holding high-tech firms are more vulnerable to contractionary monetary policy shocks. Specifically, a one-percentage-point increase in the 2-year treasury rate results in approximately a 0.5 percent decline in TFP for high-tech firms, with the negative effect becoming more pronounced when firms face financing constraints. Given that interest rate hikes are particularly harmful to high-tech firms, I recommend financial support to mitigate the adverse effects of contractionary monetary policy on these firms.
{"title":"Productivity responses of high-tech firms to monetary policy","authors":"M. Jahangir Alam","doi":"10.1016/j.najef.2025.102519","DOIUrl":"10.1016/j.najef.2025.102519","url":null,"abstract":"<div><div>This paper examines the effect of monetary policy shocks on the Total Factor Productivity (TFP) of high-tech versus low-tech firms, focusing on how changes in borrowing costs and credit availability influence productivity. To isolate the causal effect, I use firm-level longitudinal data from <em>Compustat</em>’s publicly listed firms and apply the Local Projections-Instrumental Variables (LP-IV) approach, with high-frequency interest rate surprises serving as instrumental variables. The results indicate that smaller, younger, and low-cash-holding high-tech firms are more vulnerable to contractionary monetary policy shocks. Specifically, a one-percentage-point increase in the 2-year treasury rate results in approximately a 0.5 percent decline in TFP for high-tech firms, with the negative effect becoming more pronounced when firms face financing constraints. Given that interest rate hikes are particularly harmful to high-tech firms, I recommend financial support to mitigate the adverse effects of contractionary monetary policy on these firms.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"80 ","pages":"Article 102519"},"PeriodicalIF":3.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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