Pub Date : 2025-12-01Epub Date: 2025-11-15DOI: 10.1016/j.qref.2025.102076
Bruno Morier , Pedro L. Valls Pereira
In this paper, we develop a new model for forecasting high-frequency, intraday, conditional, discrete return densities and volatility using deep learning. Specifically, we model the conditional distribution using a modified Skellam distribution, where the mean follows an auto-regressive specification. We then train feed-forward neural networks to generate predictions for the underlying high-frequency volatility. We test four different specifications, including different sets of features and parameters. Then, we conduct a comprehensive walk-forward forecasting experiment to compare the forecasting accuracy of the proposed models. All of the proposed models outperform the empirical non-parametric forecasting rules considered. The new forecasting procedure also provides better out-of-sample forecasts compared to all state space models based on Koopman et al. (2017). We conclude that the bid–ask spread, high-low interval spread, and the volume traded are predictive variables for the volatility process. According to our model estimates, these variables appear to have a positive non-linear S-shaped relationship with volatility.
{"title":"Forecasting intraday volatility and densities using deep learning","authors":"Bruno Morier , Pedro L. Valls Pereira","doi":"10.1016/j.qref.2025.102076","DOIUrl":"10.1016/j.qref.2025.102076","url":null,"abstract":"<div><div>In this paper, we develop a new model for forecasting high-frequency, intraday, conditional, discrete return densities and volatility using deep learning. Specifically, we model the conditional distribution using a modified Skellam distribution, where the mean follows an auto-regressive specification. We then train feed-forward neural networks to generate predictions for the underlying high-frequency volatility. We test four different specifications, including different sets of features and parameters. Then, we conduct a comprehensive walk-forward forecasting experiment to compare the forecasting accuracy of the proposed models. All of the proposed models outperform the empirical non-parametric forecasting rules considered. The new forecasting procedure also provides better out-of-sample forecasts compared to all state space models based on Koopman et al. (2017). We conclude that the bid–ask spread, high-low interval spread, and the volume traded are predictive variables for the volatility process. According to our model estimates, these variables appear to have a positive non-linear S-shaped relationship with volatility.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102076"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578874","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 : 2025-12-01Epub Date: 2025-09-03DOI: 10.1016/j.qref.2025.102042
Langang Feng , Jin Hu , Minmin Huang , Muhammad Irfan , Mingjun Hu
This paper explores how artificial intelligence (AI) drives corporate innovation. Using a procurement‑based AI adoption index, patent records, and supply‑chain data from 4004 A-share firms over 2011–2023, we find that greater AI adoption significantly increases the output and efficiency of firms' innovation. We propose a dual‑channel model in which AI enhances knowledge creation and reuse (knowledge orchestration) and transforms data into actionable environmental assets (data assetization). Heterogeneity analysis reveals that large incumbents and growth‑stage firms leverage AI most effectively for innovation outputs and efficiency. Further analysis shows that AI-driven innovation is amplified in firms with executives who have information technology backgrounds, and that highly innovative firms diversify their supply chain to reduce resource risk. Our results demonstrate AI’s potential to advance corporate innovation. We conclude with policy recommendations for municipal planners and corporate strategists to enhance firms’ competitive advantage and promote the development of AI.
{"title":"From algorithms to invention: AI’s impact on corporate innovation output and efficiency","authors":"Langang Feng , Jin Hu , Minmin Huang , Muhammad Irfan , Mingjun Hu","doi":"10.1016/j.qref.2025.102042","DOIUrl":"10.1016/j.qref.2025.102042","url":null,"abstract":"<div><div>This paper explores how artificial intelligence (AI) drives corporate innovation. Using a procurement‑based AI adoption index, patent records, and supply‑chain data from 4004 A-share firms over 2011–2023, we find that greater AI adoption significantly increases the output and efficiency of firms' innovation. We propose a dual‑channel model in which AI enhances knowledge creation and reuse (knowledge orchestration) and transforms data into actionable environmental assets (data assetization). Heterogeneity analysis reveals that large incumbents and growth‑stage firms leverage AI most effectively for innovation outputs and efficiency. Further analysis shows that AI-driven innovation is amplified in firms with executives who have information technology backgrounds, and that highly innovative firms diversify their supply chain to reduce resource risk. Our results demonstrate AI’s potential to advance corporate innovation. We conclude with policy recommendations for municipal planners and corporate strategists to enhance firms’ competitive advantage and promote the development of AI.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102042"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027800","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 : 2025-12-01Epub Date: 2025-11-15DOI: 10.1016/j.qref.2025.102077
Miaoyin (Alexandra) Zhang
This paper examines the role of marketplace lending (MPL) as an alternative credit provider during the COVID-19 pandemic. Exploiting variation in monthly COVID-19 exposure across US counties, we find that counties with larger COVID-19 exposure experience higher MPL lending volume. This relationship is more pronounced in areas with more constrained banking, suggesting that marketplace lenders fill borrowing needs in underbanked areas and therefore substitute for the traditional lending sector. However, in contrast to prior work showing that marketplace lenders typically increase credit availability to riskier borrowers in normal times, we find that the increase in loans primarily goes to higher credit-quality borrowers during the pandemic. This result is consistent with a "flight-to-quality" reaction. Additionally, there is some evidence of altruistic lending behaviors, as medical-related loans increase in areas more affected by the pandemic.
{"title":"Does marketplace lending provide liquidity during a crisis?","authors":"Miaoyin (Alexandra) Zhang","doi":"10.1016/j.qref.2025.102077","DOIUrl":"10.1016/j.qref.2025.102077","url":null,"abstract":"<div><div>This paper examines the role of marketplace lending (MPL) as an alternative credit provider during the COVID-19 pandemic. Exploiting variation in monthly COVID-19 exposure across US counties, we find that counties with larger COVID-19 exposure experience higher MPL lending volume. This relationship is more pronounced in areas with more constrained banking, suggesting that marketplace lenders fill borrowing needs in underbanked areas and therefore substitute for the traditional lending sector. However, in contrast to prior work showing that marketplace lenders typically increase credit availability to riskier borrowers in normal times, we find that the increase in loans primarily goes to higher credit-quality borrowers during the pandemic. This result is consistent with a \"flight-to-quality\" reaction. Additionally, there is some evidence of altruistic lending behaviors, as medical-related loans increase in areas more affected by the pandemic.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102077"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623633","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 : 2025-12-01Epub Date: 2025-10-19DOI: 10.1016/j.qref.2025.102067
Yufei Gan
Amidst an escalating global biodiversity crisis and a proliferation of corporate environmental claims, this study addresses a critical gap between symbolic corporate communication and its substantive ecological impact. We establish a causal link between corporate greenwashing and increased biodiversity risk using a panel of 17,076 firm-year observations for Chinese listed companies from 2015 to 2024. To ensure robust causal inference, we employ a rigorous identification strategy centered on a Multiple-Difference-in-Differences (M-DID) design, which is complemented by Propensity Score Matching (PSM), an Instrumental Variable (IV) approach, and placebo tests. Our findings reveal that greenwashing causally increases biodiversity risk through a dual-pathway mechanism. Internally, it fosters a "green technology innovation bubble," prioritizing patent quantity over quality. Externally, it degrades "environmental disclosure quality," shielding harmful operations from scrutiny. This detrimental relationship is attenuated by CEOs with green experience but exacerbated by managerial myopia. Our research bridges a crucial theoretical divide between impression management and real-world ecological outcomes, offering vital insights for regulators and investors seeking to curb specious environmentalism.
{"title":"When green claims turn brown: The Impact of corporate greenwashing on biodiversity risk in China","authors":"Yufei Gan","doi":"10.1016/j.qref.2025.102067","DOIUrl":"10.1016/j.qref.2025.102067","url":null,"abstract":"<div><div>Amidst an escalating global biodiversity crisis and a proliferation of corporate environmental claims, this study addresses a critical gap between symbolic corporate communication and its substantive ecological impact. We establish a causal link between corporate greenwashing and increased biodiversity risk using a panel of 17,076 firm-year observations for Chinese listed companies from 2015 to 2024. To ensure robust causal inference, we employ a rigorous identification strategy centered on a Multiple-Difference-in-Differences (M-DID) design, which is complemented by Propensity Score Matching (PSM), an Instrumental Variable (IV) approach, and placebo tests. Our findings reveal that greenwashing causally increases biodiversity risk through a dual-pathway mechanism. Internally, it fosters a \"green technology innovation bubble,\" prioritizing patent quantity over quality. Externally, it degrades \"environmental disclosure quality,\" shielding harmful operations from scrutiny. This detrimental relationship is attenuated by CEOs with green experience but exacerbated by managerial myopia. Our research bridges a crucial theoretical divide between impression management and real-world ecological outcomes, offering vital insights for regulators and investors seeking to curb specious environmentalism.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102067"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417297","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 : 2025-12-01Epub Date: 2025-10-22DOI: 10.1016/j.qref.2025.102071
Roland von Horn , Muhamed Kudic
Systemic risk in banking has drawn worldwide attention since the 2007–2009 crisis. Fintech startups provide cutting-edge solutions that extend beyond banks’ traditional capabilities, fostering intensive bank–fintech cooperation and giving rise to a ‘pervaded banking system’ (PBS) with novel, largely uncharted vulnerabilities. Using complex adaptive systems theory, we assemble a dataset of 604 fintechs and 802 banks in Central Europe (DACH-Region – Germany, Austria, and Switzerland) – and propose a structurally defined stability concept. We evaluate PBS stability through multiple network-based stress-testing scenarios. The results show that large-scale fintech failures can trigger severe systemic disruptions, whereas exits of small and recently established fintechs have limited effects. By contrast, fintech firms occupying structurally exposed positions act as key risk amplifiers, a channel that traditional risk assessments largely overlook. Our framework thus complements conventional market-based or balance-sheet-based approaches by uncovering structure-induced vulnerabilities in the financial system.
{"title":"Systemic risk in the fintech-banking system: Assessing instabilities and vulnerabilities in Central Europe","authors":"Roland von Horn , Muhamed Kudic","doi":"10.1016/j.qref.2025.102071","DOIUrl":"10.1016/j.qref.2025.102071","url":null,"abstract":"<div><div>Systemic risk in banking has drawn worldwide attention since the 2007–2009 crisis. Fintech startups provide cutting-edge solutions that extend beyond banks’ traditional capabilities, fostering intensive bank–fintech cooperation and giving rise to a ‘pervaded banking system’ (PBS) with novel, largely uncharted vulnerabilities. Using complex adaptive systems theory, we assemble a dataset of 604 fintechs and 802 banks in Central Europe (DACH-Region – Germany, Austria, and Switzerland) – and propose a structurally defined stability concept. We evaluate PBS stability through multiple network-based stress-testing scenarios. The results show that large-scale fintech failures can trigger severe systemic disruptions, whereas exits of small and recently established fintechs have limited effects. By contrast, fintech firms occupying structurally exposed positions act as key risk amplifiers, a channel that traditional risk assessments largely overlook. Our framework thus complements conventional market-based or balance-sheet-based approaches by uncovering structure-induced vulnerabilities in the financial system.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102071"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578873","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 : 2025-12-01Epub Date: 2025-09-23DOI: 10.1016/j.qref.2025.102055
I-Chan Chiu , Mao-Wei Hung , Kuang-Chieh Yen
The literature rarely addresses the correlation between option-implied information in the stock and cryptocurrency markets. This study introduces VMS, defined as the difference between the squared VIX and SVIX indices, which captures the left-tail risk of the stock market (Martin, 2017). Analyzing data from 2014 to 2022, we find that higher VMS predicts increased excess returns in the cryptocurrency market. This relationship remains robust when controlling for economic policy uncertainty (Baker, et al., 2016) and the VIX premium (Cheng, 2019), with no significant impacts from crypto-size or crypto-momentum factors.
文献很少涉及股票和加密货币市场中期权隐含信息之间的相关性。本研究引入了VMS，定义为VIX指数和VIX指数的平方之差，它捕获了股票市场的左尾风险（Martin, 2017）。分析2014年至2022年的数据，我们发现更高的VMS预示着加密货币市场的超额回报会增加。在控制经济政策不确定性（Baker, et al., 2016）和VIX溢价（Cheng, 2019）时，这种关系仍然稳固，加密货币规模或加密货币动量因素没有显著影响。
{"title":"SVIX, VIX, and cryptocurrency market return","authors":"I-Chan Chiu , Mao-Wei Hung , Kuang-Chieh Yen","doi":"10.1016/j.qref.2025.102055","DOIUrl":"10.1016/j.qref.2025.102055","url":null,"abstract":"<div><div>The literature rarely addresses the correlation between option-implied information in the stock and cryptocurrency markets. This study introduces <em>VMS</em>, defined as the difference between the squared VIX and SVIX indices, which captures the left-tail risk of the stock market (Martin, 2017). Analyzing data from 2014 to 2022, we find that higher <em>VMS</em> predicts increased excess returns in the cryptocurrency market. This relationship remains robust when controlling for economic policy uncertainty (Baker, et al., 2016) and the VIX premium (Cheng, 2019), with no significant impacts from crypto-size or crypto-momentum factors.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102055"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267523","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 : 2025-12-01Epub Date: 2025-10-10DOI: 10.1016/j.qref.2025.102060
Divya P. Tulsyan , Mayank Joshipura , Anil V. Mishra
This study investigates the presence of a risk anomaly in the Indian stock market and examines whether profitability can explain this anomaly. Using Nifty 500 index companies from March 2003 to June 2022, the study concludes that: a) the risk anomaly is present in the Indian stock markets and manifests in the form of a lack of a risk-return relationship; b) higher profitability enhances absolute and risk-adjusted performance; c) high-volatility stocks tend to have lower profitability, while low-volatility stocks often exhibit higher profitability; d) the positive risk-return relationship is not restored after controlling for profitability; e) after accounting for profitability, the risk anomaly moderates but still fails to resolve the puzzle. The study is relevant for investors, scholars, and money managers, and it offers insights into the existing debate on the role of profitability in the emerging market context.
{"title":"Does profitability explain the low-risk anomaly in India?","authors":"Divya P. Tulsyan , Mayank Joshipura , Anil V. Mishra","doi":"10.1016/j.qref.2025.102060","DOIUrl":"10.1016/j.qref.2025.102060","url":null,"abstract":"<div><div>This study investigates the presence of a risk anomaly in the Indian stock market and examines whether profitability can explain this anomaly. Using Nifty 500 index companies from March 2003 to June 2022, the study concludes that: a) the risk anomaly is present in the Indian stock markets and manifests in the form of a lack of a risk-return relationship; b) higher profitability enhances absolute and risk-adjusted performance; c) high-volatility stocks tend to have lower profitability, while low-volatility stocks often exhibit higher profitability; d) the positive risk-return relationship is not restored after controlling for profitability; e) after accounting for profitability, the risk anomaly moderates but still fails to resolve the puzzle. The study is relevant for investors, scholars, and money managers, and it offers insights into the existing debate on the role of profitability in the emerging market context.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102060"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267522","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 : 2025-12-01Epub Date: 2025-10-30DOI: 10.1016/j.qref.2025.102072
Werley Cordeiro , João F. Caldeira , Guilherme V. Moura
This paper presents a model of the term structure of interest rates that incorporates expectations regarding macroeconomic data to capture yield dynamics, while also accounting for time-varying volatility. Our findings demonstrate that including survey data on market participants’ expectations significantly improves the out-of-sample forecasting performance of the model, as shown by statistical measures of predictive accuracy. Furthermore, we assess the economic value of yield curve predictability through a portfolio allocation exercise. The results indicate that considering time-varying yield volatility is crucial and significantly enhances the economic relevance of forecasts, regardless of the level of risk aversion assumed.
{"title":"Forecasting the Brazilian yield curve using macroeconomics expectations and time-varying volatility","authors":"Werley Cordeiro , João F. Caldeira , Guilherme V. Moura","doi":"10.1016/j.qref.2025.102072","DOIUrl":"10.1016/j.qref.2025.102072","url":null,"abstract":"<div><div>This paper presents a model of the term structure of interest rates that incorporates expectations regarding macroeconomic data to capture yield dynamics, while also accounting for time-varying volatility. Our findings demonstrate that including survey data on market participants’ expectations significantly improves the out-of-sample forecasting performance of the model, as shown by statistical measures of predictive accuracy. Furthermore, we assess the economic value of yield curve predictability through a portfolio allocation exercise. The results indicate that considering time-varying yield volatility is crucial and significantly enhances the economic relevance of forecasts, regardless of the level of risk aversion assumed.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102072"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525839","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 : 2025-12-01Epub Date: 2025-10-26DOI: 10.1016/j.qref.2025.102070
Jauling Tseng
This study investigates the influence and quantile differences of key variables on crowdfunding campaign fundraising volumes by using data from 73,146 campaigns across major global platforms in developed, developing, and emerging crowdfunding markets from 2012 to 2017. The results indicate that campaigns with lower funding targets, longer financing periods, more social media followers, backers, photos, and comments, more frequent updates and past successful experiences, and fewer past failure experiences are significantly more likely to succeed. Additionally, campaigns with longer financing periods, more social media followers, backers, comments, frequent updates, and past successful experiences, and fewer past failure experiences are likely to raise higher fundraising volumes. Moreover, campaigns in developed crowdfunding markets are significantly more likely to succeed and raise large volumes of funds compared with those in developing markets, whereas those in emerging markets are more likely to succeed but raise lower volumes of funds than those in developing markets. Finally, for campaigns in the highest 90th quantile of successful funding volumes, improvements in campaign variables lead to greater marginal increases in funding volumes compared with those in the lowest 10th quantile, highlighting substantial quantile differences and unequal effects across funding levels. This study provides insights that can guide start-ups and policymakers in developing effective crowdfunding strategies and policies, thereby promoting the healthy development of crowdfunding markets and improving financial inclusion.
{"title":"Factors and quantile differences influencing funding volumes of successful crowdfunding campaigns on reward-based platforms in developed, developing, and emerging crowdfunding markets","authors":"Jauling Tseng","doi":"10.1016/j.qref.2025.102070","DOIUrl":"10.1016/j.qref.2025.102070","url":null,"abstract":"<div><div>This study investigates the influence and quantile differences of key variables on crowdfunding campaign fundraising volumes by using data from 73,146 campaigns across major global platforms in developed, developing, and emerging crowdfunding markets from 2012 to 2017. The results indicate that campaigns with lower funding targets, longer financing periods, more social media followers, backers, photos, and comments, more frequent updates and past successful experiences, and fewer past failure experiences are significantly more likely to succeed. Additionally, campaigns with longer financing periods, more social media followers, backers, comments, frequent updates, and past successful experiences, and fewer past failure experiences are likely to raise higher fundraising volumes. Moreover, campaigns in developed crowdfunding markets are significantly more likely to succeed and raise large volumes of funds compared with those in developing markets, whereas those in emerging markets are more likely to succeed but raise lower volumes of funds than those in developing markets. Finally, for campaigns in the highest 90th quantile of successful funding volumes, improvements in campaign variables lead to greater marginal increases in funding volumes compared with those in the lowest 10th quantile, highlighting substantial quantile differences and unequal effects across funding levels. This study provides insights that can guide start-ups and policymakers in developing effective crowdfunding strategies and policies, thereby promoting the healthy development of crowdfunding markets and improving financial inclusion.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"104 ","pages":"Article 102070"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525840","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: 2025-06-04DOI: 10.1016/j.qref.2025.102012
Lorenzo Castellani , Francesco Decarolis , Gabriele Rovigatti
This paper analyzes how local public authorities in Italy responded to recent procurement centralization reforms. Using detailed data on all Italian public contracts awarded between 2015 and 2017, we document three types of strategic behavior aimed at retaining local autonomy. First, authorities anticipating the reforms accelerated purchases to avoid central oversight. Second, they manipulated contract values to remain below monetary thresholds. Third, when required to centralize, they often chose the least centralized forms of coordination. These findings highlight how institutional design and local incentives can blunt the intended effects of centralization policies, offering broader lessons for procurement reform across the EU.
{"title":"Local government responses to procurement centralization: Evidence from Italy","authors":"Lorenzo Castellani , Francesco Decarolis , Gabriele Rovigatti","doi":"10.1016/j.qref.2025.102012","DOIUrl":"10.1016/j.qref.2025.102012","url":null,"abstract":"<div><div>This paper analyzes how local public authorities in Italy responded to recent procurement centralization reforms. Using detailed data on all Italian public contracts awarded between 2015 and 2017, we document three types of strategic behavior aimed at retaining local autonomy. First, authorities anticipating the reforms accelerated purchases to avoid central oversight. Second, they manipulated contract values to remain below monetary thresholds. Third, when required to centralize, they often chose the least centralized forms of coordination. These findings highlight how institutional design and local incentives can blunt the intended effects of centralization policies, offering broader lessons for procurement reform across the EU.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"103 ","pages":"Article 102012"},"PeriodicalIF":2.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313076","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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