Pub Date : 2026-02-01Epub Date: 2025-11-27DOI: 10.1016/j.jempfin.2025.101671
Luca Vincenzo Ballestra , Enzo D’Innocenzo , Christian Tezza
We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices. The code for estimating the model, as well as for computing option prices, is made accessible in MATLAB language.1
{"title":"A GARCH model with two volatility components and two driving factors","authors":"Luca Vincenzo Ballestra , Enzo D’Innocenzo , Christian Tezza","doi":"10.1016/j.jempfin.2025.101671","DOIUrl":"10.1016/j.jempfin.2025.101671","url":null,"abstract":"<div><div>We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices. The code for estimating the model, as well as for computing option prices, is made accessible in MATLAB language.<span><span><sup>1</sup></span></span></div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101671"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-08DOI: 10.1016/j.jempfin.2025.101683
Xiaolin Ye, Baibing Li, Kai-Hong Tee
A distinctive feature of hedge funds is their dynamic style of trading; hedge funds may shift the investment style in their lifetime. Style shifting is a strategic decision for funds which is beyond the more traditional stock-picking and market-timing carried out at the operational level. This paper tests and validates the performance implications of style-selection skill of hedge funds. Based on the trading style identification through Probabilistic Principal Component Analysis and the measure of style-selection skill developed in this paper, we find that such skill has predictive power for future fund performance, persisting for up to one year. In addition, our findings reveal that funds exhibiting greater style-selection skill enhance the probability of survival. Furthermore, we show that smaller, solo-managed funds operated by managers with longer tenure and higher management fees tend to have greater style-selection skill. Our findings support investors’ decisions when selecting hedge funds. It also opens a new perspective for managerial skills in active money management, reflecting managers’ expertise in data processing about micro and macro information and shocks to achieve success, when considering the investment style.
{"title":"On evaluating the style-selection skill of hedge funds","authors":"Xiaolin Ye, Baibing Li, Kai-Hong Tee","doi":"10.1016/j.jempfin.2025.101683","DOIUrl":"10.1016/j.jempfin.2025.101683","url":null,"abstract":"<div><div>A distinctive feature of hedge funds is their dynamic style of trading; hedge funds may shift the investment style in their lifetime. Style shifting is a strategic decision for funds which is beyond the more traditional stock-picking and market-timing carried out at the operational level. This paper tests and validates the performance implications of style-selection skill of hedge funds. Based on the trading style identification through Probabilistic Principal Component Analysis and the measure of style-selection skill developed in this paper, we find that such skill has predictive power for future fund performance, persisting for up to one year. In addition, our findings reveal that funds exhibiting greater style-selection skill enhance the probability of survival. Furthermore, we show that smaller, solo-managed funds operated by managers with longer tenure and higher management fees tend to have greater style-selection skill. Our findings support investors’ decisions when selecting hedge funds. It also opens a new perspective for managerial skills in active money management, reflecting managers’ expertise in data processing about micro and macro information and shocks to achieve success, when considering the investment style.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101683"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-11-28DOI: 10.1016/j.jempfin.2025.101668
Moritz Dauber, Jochen Lawrenz
We revisit the ability of the consumption–wealth ratio () to forecast stock market returns and document a substantial decline in predictability over the last two decades. This decay of goes along with a structural shift in the underlying cointegration relationship, which can be attributed to the fact that asset wealth evolves increasingly detached from aggregate consumption and labor income. We propose a new version of derived only from the top 10% richest households and show that among various other proposed improvements of , this appears as the most promising empirical proxy for the still appealing theory.
{"title":"The decay of cay","authors":"Moritz Dauber, Jochen Lawrenz","doi":"10.1016/j.jempfin.2025.101668","DOIUrl":"10.1016/j.jempfin.2025.101668","url":null,"abstract":"<div><div>We revisit the ability of the consumption–wealth ratio (<span><math><mrow><mi>c</mi><mi>a</mi><mi>y</mi></mrow></math></span>) to forecast stock market returns and document a substantial decline in predictability over the last two decades. This decay of <span><math><mrow><mi>c</mi><mi>a</mi><mi>y</mi></mrow></math></span> goes along with a structural shift in the underlying cointegration relationship, which can be attributed to the fact that asset wealth evolves increasingly detached from aggregate consumption and labor income. We propose a new version of <span><math><mrow><mi>c</mi><mi>a</mi><mi>y</mi></mrow></math></span> derived only from the top 10% richest households and show that among various other proposed improvements of <span><math><mrow><mi>c</mi><mi>a</mi><mi>y</mi></mrow></math></span>, this appears as the most promising empirical proxy for the still appealing theory.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101668"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-16DOI: 10.1016/j.jempfin.2026.101686
Xuejun Jin , Yifan Chen , Xiaobin Liu , Tao Zeng
We investigate the cross-section of Chinese corporate bond returns using reduced-rank regression analysis (RRA) proposed by He et al. (2022). We collect 31 individual bond characteristics documented in the prior literature and construct 34 bond portfolios. Empirically, we find that an RRA three-factor model outperforms traditional factor models, and competing dimension-reduction methods (PCA and PLS) both in-sample and out-of-sample. The bond market factor is the dominant predictor, accounting for approximately 80% of the total explanatory power of RRA models, while other factors provide limited incremental pricing information, highlighting the need to find new bond factors. Furthermore, equity anomalies fail to improve the explanatory power of RRA models, only partially explaining the systematic component of bond returns within the RRA framework while providing negligible information for the idiosyncratic component.
{"title":"Factors in the cross-section of Chinese corporate bonds: Evidence from reduced-rank analysis","authors":"Xuejun Jin , Yifan Chen , Xiaobin Liu , Tao Zeng","doi":"10.1016/j.jempfin.2026.101686","DOIUrl":"10.1016/j.jempfin.2026.101686","url":null,"abstract":"<div><div>We investigate the cross-section of Chinese corporate bond returns using reduced-rank regression analysis (RRA) proposed by He et al. (2022). We collect 31 individual bond characteristics documented in the prior literature and construct 34 bond portfolios. Empirically, we find that an RRA three-factor model outperforms traditional factor models, and competing dimension-reduction methods (PCA and PLS) both in-sample and out-of-sample. The bond market factor is the dominant predictor, accounting for approximately 80% of the total explanatory power of RRA models, while other factors provide limited incremental pricing information, highlighting the need to find new bond factors. Furthermore, equity anomalies fail to improve the explanatory power of RRA models, only partially explaining the systematic component of bond returns within the RRA framework while providing negligible information for the idiosyncratic component.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101686"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-17DOI: 10.1016/j.jempfin.2025.101652
Wei Hou, Esad Smajlbegovic, Daniel Urban
Researchers need to decide on which academic conferences to attend. To inform this decision, we track the publication status of 6805 research articles presented at 87 finance conferences between 2011 and 2015. We rank these conferences based on publication rates in top finance and economics journals. To complement these rankings, we also examine publication rates within specific research fields and citation scores. The rankings show considerable heterogeneity in conference quality and uncover three major conference clusters. We further examine the role and timing of conferences in the publication process, analyze important time trends, explore the relationship between conference size and publication success, and highlight the relatively low overlap in accepted papers across conferences.
{"title":"Ranking finance conferences: An update","authors":"Wei Hou, Esad Smajlbegovic, Daniel Urban","doi":"10.1016/j.jempfin.2025.101652","DOIUrl":"10.1016/j.jempfin.2025.101652","url":null,"abstract":"<div><div>Researchers need to decide on which academic conferences to attend. To inform this decision, we track the publication status of 6805 research articles presented at 87 finance conferences between 2011 and 2015. We rank these conferences based on publication rates in top finance and economics journals. To complement these rankings, we also examine publication rates within specific research fields and citation scores. The rankings show considerable heterogeneity in conference quality and uncover three major conference clusters. We further examine the role and timing of conferences in the publication process, analyze important time trends, explore the relationship between conference size and publication success, and highlight the relatively low overlap in accepted papers across conferences.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101652"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-11-20DOI: 10.1016/j.jempfin.2025.101672
Nicola Bartolini, Silvia Romagnoli, Amia Santini
This study explores how climate-related risk factors influence the European equity and fixed-income markets. We examine the effect of specific physical risk drivers, including temperature fluctuations, drought, floods, wind, and wildfire risk, on both stocks and bonds. Additionally, we assess the impact of transition risk using two potential indicators: the log-returns of futures on European Carbon Allowances and a Transition Risk Index derived from credit default spreads. We also compare them to see if they carry the same information. Our findings reveal that climate risk variables have different effects on stocks and bonds, with stock returns appearing mostly unaffected by climate-related variables. In contrast, bond z-spreads show significant statistical relationships with both physical and transition climate risks. Physical risk, on average, rewards the green bonds in the sample, and penalizes the traditional bonds. As for transition risk, the two proxies are shown to capture different types of information and to affect different bonds. This suggests that credit default swaps are pricing a transition risk that goes beyond carbon emissions.
{"title":"Understanding climate risk in Europe: Are transition and physical risk priced in equity and fixed-income markets?","authors":"Nicola Bartolini, Silvia Romagnoli, Amia Santini","doi":"10.1016/j.jempfin.2025.101672","DOIUrl":"10.1016/j.jempfin.2025.101672","url":null,"abstract":"<div><div>This study explores how climate-related risk factors influence the European equity and fixed-income markets. We examine the effect of specific physical risk drivers, including temperature fluctuations, drought, floods, wind, and wildfire risk, on both stocks and bonds. Additionally, we assess the impact of transition risk using two potential indicators: the log-returns of futures on European Carbon Allowances and a Transition Risk Index derived from credit default spreads. We also compare them to see if they carry the same information. Our findings reveal that climate risk variables have different effects on stocks and bonds, with stock returns appearing mostly unaffected by climate-related variables. In contrast, bond z-spreads show significant statistical relationships with both physical and transition climate risks. Physical risk, on average, rewards the green bonds in the sample, and penalizes the traditional bonds. As for transition risk, the two proxies are shown to capture different types of information and to affect different bonds. This suggests that credit default swaps are pricing a transition risk that goes beyond carbon emissions.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101672"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-10DOI: 10.1016/j.jempfin.2025.101664
Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao
We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.
{"title":"Media, inventors, and corporate innovation","authors":"Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao","doi":"10.1016/j.jempfin.2025.101664","DOIUrl":"10.1016/j.jempfin.2025.101664","url":null,"abstract":"<div><div>We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101664"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-10DOI: 10.1016/j.jempfin.2025.101650
Riccardo Rebonato , Ken Nyholm
We explain why the Cochrane–Piazzesi (CP) model, which uses a single tent-shaped linear combination of forward rates, is so effective at predicting bond excess returns. By using a novel statistical test coupled with a popular resampling technique, first we rule out the possibility that the high predictability may be an artefact of in-sample overfitting. Then we find that, contrary to explanations proposed in the original CP paper, neither the specific tent shape of the factor loadings nor the four-to-five-year yield spread are essential for the model’s predictive power. Instead, our analysis suggests that the predictive power of the CP model lies in its ability to identify the cointegration relationship among the quasi-unit-root forward rate regressors needed to produce the stationary process of excess returns. To support this interpretation we show that cointegration relationships among forward rates directly provide strong predictors of excess returns, and we propose that the cointegration modes of attraction generate at least part of the excess returns. Our findings shed new light on the source of bond return predictability captured by the CP factor and highlight the link between cointegration properties and the dynamics of yields.1
{"title":"Why does the Cochrane–Piazzesi model predict treasury returns?","authors":"Riccardo Rebonato , Ken Nyholm","doi":"10.1016/j.jempfin.2025.101650","DOIUrl":"10.1016/j.jempfin.2025.101650","url":null,"abstract":"<div><div>We explain why the Cochrane–Piazzesi (CP) model, which uses a single tent-shaped linear combination of forward rates, is so effective at predicting bond excess returns. By using a novel statistical test coupled with a popular resampling technique, first we rule out the possibility that the high predictability may be an artefact of in-sample overfitting. Then we find that, contrary to explanations proposed in the original CP paper, neither the specific tent shape of the factor loadings nor the four-to-five-year yield spread are essential for the model’s predictive power. Instead, our analysis suggests that the predictive power of the CP model lies in its ability to identify the cointegration relationship among the quasi-unit-root forward rate regressors needed to produce the stationary process of excess returns. To support this interpretation we show that cointegration relationships among forward rates directly provide strong predictors of excess returns, and we propose that the cointegration modes of attraction generate at least part of the excess returns. Our findings shed new light on the source of bond return predictability captured by the CP factor and highlight the link between cointegration properties and the dynamics of yields.<span><span><sup>1</sup></span></span></div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101650"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-10DOI: 10.1016/j.jempfin.2025.101663
Mengmeng Dong
I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to -means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.
{"title":"Economic aggregation of return signals in global markets","authors":"Mengmeng Dong","doi":"10.1016/j.jempfin.2025.101663","DOIUrl":"10.1016/j.jempfin.2025.101663","url":null,"abstract":"<div><div>I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to <span><math><mi>k</mi></math></span>-means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101663"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-05DOI: 10.1016/j.jempfin.2025.101665
Yunqi Zhang , Yu Meng , Xiaoyu Zhang
Bankruptcy abuse prevention has been criticized for increasing foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention reduces household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.
{"title":"Household debt overhang and bankruptcy abuse prevention","authors":"Yunqi Zhang , Yu Meng , Xiaoyu Zhang","doi":"10.1016/j.jempfin.2025.101665","DOIUrl":"10.1016/j.jempfin.2025.101665","url":null,"abstract":"<div><div>Bankruptcy abuse prevention has been criticized for <em>increasing</em> foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention <em>reduces</em> household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101665"},"PeriodicalIF":2.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号