Pub Date : 2025-10-31DOI: 10.1016/j.jfineco.2025.104191
Christian Heyerdahl-Larsen , Philipp Illeditsch
Disagreement about macroeconomic fundamentals accounts for only part of the disagreement about future interest rates, creating a “disagreement correlation” puzzle. This puzzle arises because standard equilibrium models with belief differences predict a strong link between asset return disagreement and fundamental disagreement, a link not supported by the data. We address this puzzle by introducing a model where disagreement about future demand for savings—driven by disagreement over the prevalence of patient versus impatient investors in the economy—generates asset return disagreement. Our mechanism produces stochastic yield volatility, time-varying bond risk premia, and an upward-sloping yield curve. Empirically, we construct a proxy for demand disagreement by isolating the component of yield disagreement unrelated to disagreement about macro-fundamentals. This proxy is positively related to yields and their volatilities, and predicts future bond risk premia, consistent with the predictions of our demand disagreement model.
{"title":"Demand disagreement","authors":"Christian Heyerdahl-Larsen , Philipp Illeditsch","doi":"10.1016/j.jfineco.2025.104191","DOIUrl":"10.1016/j.jfineco.2025.104191","url":null,"abstract":"<div><div>Disagreement about macroeconomic fundamentals accounts for only part of the disagreement about future interest rates, creating a “disagreement correlation” puzzle. This puzzle arises because standard equilibrium models with belief differences predict a strong link between asset return disagreement and fundamental disagreement, a link not supported by the data. We address this puzzle by introducing a model where disagreement about future demand for savings—driven by disagreement over the prevalence of patient versus impatient investors in the economy—generates asset return disagreement. Our mechanism produces stochastic yield volatility, time-varying bond risk premia, and an upward-sloping yield curve. Empirically, we construct a proxy for demand disagreement by isolating the component of yield disagreement unrelated to disagreement about macro-fundamentals. This proxy is positively related to yields and their volatilities, and predicts future bond risk premia, consistent with the predictions of our demand disagreement model.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"175 ","pages":"Article 104191"},"PeriodicalIF":10.4,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.jfineco.2025.104172
Haoyang Liu , Christopher Palmer
We document implicit extrapolation in investment decision-making that exceeds the extrapolation inferable from stated expectations. Locally experienced returns predict individual real-estate investment decisions even conditional on an investor’s forecasted home-price growth and risk aversion. Moreover, estimates of this experience effect on investment are larger than implied by the combined effect of past returns on stated expectations and stated expectations on investment. We demonstrate that heterogeneous forecast confidence helps explain why many investors rely on past returns over their survey-elicited forecasts. As their rationale, such survey respondents frequently cite intentional extrapolation or a lack of confidence in other belief factors.
{"title":"Implicit extrapolation and the beliefs channel of investment demand","authors":"Haoyang Liu , Christopher Palmer","doi":"10.1016/j.jfineco.2025.104172","DOIUrl":"10.1016/j.jfineco.2025.104172","url":null,"abstract":"<div><div>We document implicit extrapolation in investment decision-making that exceeds the extrapolation inferable from stated expectations. Locally experienced returns predict individual real-estate investment decisions even conditional on an investor’s forecasted home-price growth and risk aversion. Moreover, estimates of this experience effect on investment are larger than implied by the combined effect of past returns on stated expectations and stated expectations on investment. We demonstrate that heterogeneous forecast confidence helps explain why many investors rely on past returns over their survey-elicited forecasts. As their rationale, such survey respondents frequently cite intentional extrapolation or a lack of confidence in other belief factors.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"175 ","pages":"Article 104172"},"PeriodicalIF":10.4,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145371061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-17DOI: 10.1016/j.jfineco.2025.104182
Lena Boneva , Jakub Kastl , Filip Zikes
We study dealers’ bidding behavior in the Bank of England’s quantitative easing (QE) reverse auctions. Using a granular dataset on both accepted and rejected offers together with an equilibrium model of bidding behavior, we estimate dealers’ valuations of securities offered to the Bank of England. We also recover the rents accruing to dealers from participating in the auctions as opposed to liquidating gilts in the secondary market, thereby possibly causing prices to change. These rents or so-called ”liquidity benefits” are largest in the early phases of QE implemented during the Global Financial Crisis, suggesting that QE may be particularly effective in restoring smooth market functioning when market participants are facing large liquidity shocks. Finally, we document that dealers’ valuations vary significantly with the amount of interest rate risk acquired in the secondary gilt market before the auction and with dealers’ regulatory capital.
{"title":"Dealer balance sheets and bidding behavior in the Bank of England’s QE reverse auctions","authors":"Lena Boneva , Jakub Kastl , Filip Zikes","doi":"10.1016/j.jfineco.2025.104182","DOIUrl":"10.1016/j.jfineco.2025.104182","url":null,"abstract":"<div><div>We study dealers’ bidding behavior in the Bank of England’s quantitative easing (QE) reverse auctions. Using a granular dataset on both accepted and rejected offers together with an equilibrium model of bidding behavior, we estimate dealers’ valuations of securities offered to the Bank of England. We also recover the rents accruing to dealers from participating in the auctions as opposed to liquidating gilts in the secondary market, thereby possibly causing prices to change. These rents or so-called ”liquidity benefits” are largest in the early phases of QE implemented during the Global Financial Crisis, suggesting that QE may be particularly effective in restoring smooth market functioning when market participants are facing large liquidity shocks. Finally, we document that dealers’ valuations vary significantly with the amount of interest rate risk acquired in the secondary gilt market before the auction and with dealers’ regulatory capital.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104182"},"PeriodicalIF":10.4,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-16DOI: 10.1016/j.jfineco.2025.104171
Mark Jansen , Fabian Nagel , Constantine Yannelis , Anthony Lee Zhang
We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This increases total social welfare and transfers surplus across borrower types. We show that under certain assumptions the magnitudes of these welfare changes can be estimated using only quantity and price data. Applying our methodology to bankruptcy flag removal, we find that in a counterfactual world where bankruptcy flags are never removed from credit reports, previously-bankrupt borrowers’ surplus decreases substantially, whereas efficiency increases only modestly.
{"title":"Data and welfare in credit markets","authors":"Mark Jansen , Fabian Nagel , Constantine Yannelis , Anthony Lee Zhang","doi":"10.1016/j.jfineco.2025.104171","DOIUrl":"10.1016/j.jfineco.2025.104171","url":null,"abstract":"<div><div>We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This increases total social welfare and transfers surplus across borrower types. We show that under certain assumptions the magnitudes of these welfare changes can be estimated using only quantity and price data. Applying our methodology to bankruptcy flag removal, we find that in a counterfactual world where bankruptcy flags are never removed from credit reports, previously-bankrupt borrowers’ surplus decreases substantially, whereas efficiency increases only modestly.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104171"},"PeriodicalIF":10.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-16DOI: 10.1016/j.jfineco.2025.104186
Jean-Edouard Colliard , Co-Pierre Georg
We propose a framework to study regulatory complexity, based on concepts from computer science. We distinguish different dimensions of complexity, classify existing measures, develop new ones, compute them on three examples — Basel I, the Dodd–Frank Act, and the European Banking Authority’s reporting rules — and test them using experiments and a survey on compliance costs. We highlight two measures that capture complexity beyond the length of a regulation. We propose a quantitative approach to the policy trade-off between regulatory complexity and precision.
{"title":"Measuring regulatory complexity","authors":"Jean-Edouard Colliard , Co-Pierre Georg","doi":"10.1016/j.jfineco.2025.104186","DOIUrl":"10.1016/j.jfineco.2025.104186","url":null,"abstract":"<div><div>We propose a framework to study regulatory complexity, based on concepts from computer science. We distinguish different dimensions of complexity, classify existing measures, develop new ones, compute them on three examples — Basel I, the Dodd–Frank Act, and the European Banking Authority’s reporting rules — and test them using experiments and a survey on compliance costs. We highlight two measures that capture complexity beyond the length of a regulation. We propose a quantitative approach to the policy trade-off between regulatory complexity and precision.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104186"},"PeriodicalIF":10.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-15DOI: 10.1016/j.jfineco.2025.104185
Batchimeg Sambalaibat
This paper studies a search-based model of OTC markets in which clients with heterogeneous trading needs direct their trades to one of ex-ante identical dealers. The main insight of the paper is that the way clients sort across dealers shapes dealer-to-dealer trading patterns and, in turn, generates a core–periphery interdealer network structure. Dealers in the model become heterogeneous because they attract different clients in equilibrium. Some dealers attract clients who trade frequently (e.g., index funds); others attract clients with infrequent trading needs (e.g., pension funds). Dealers attracting clients with frequent trading needs receive a larger volume of client orders, trade more with other dealers, and, as a result, form the core of the interdealer network. Conversely, dealers specializing in clients with infrequent trading needs form the periphery. I also show that accounting for client heterogeneity across dealers (a) challenges standard measurements and interpretations of bid–ask spreads and (b) generates predictions on bid–ask spreads and dealer centrality consistent with the empirical literature.
{"title":"Heterogeneous clienteles and dealer networks","authors":"Batchimeg Sambalaibat","doi":"10.1016/j.jfineco.2025.104185","DOIUrl":"10.1016/j.jfineco.2025.104185","url":null,"abstract":"<div><div>This paper studies a search-based model of OTC markets in which clients with heterogeneous trading needs direct their trades to one of ex-ante identical dealers. The main insight of the paper is that the way clients sort across dealers shapes dealer-to-dealer trading patterns and, in turn, generates a core–periphery interdealer network structure. Dealers in the model become heterogeneous because they attract different clients in equilibrium. Some dealers attract clients who trade frequently (e.g., index funds); others attract clients with infrequent trading needs (e.g., pension funds). Dealers attracting clients with frequent trading needs receive a larger volume of client orders, trade more with other dealers, and, as a result, form the core of the interdealer network. Conversely, dealers specializing in clients with infrequent trading needs form the periphery. I also show that accounting for client heterogeneity across dealers (a) challenges standard measurements and interpretations of bid–ask spreads and (b) generates predictions on bid–ask spreads and dealer centrality consistent with the empirical literature.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104185"},"PeriodicalIF":10.4,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-14DOI: 10.1016/j.jfineco.2025.104184
Riccardo Colacito , Yan Qian , Andreas Stathopoulos
We document that the currency denomination of the debt of large firms in developed countries is strongly associated with the geographical distribution of their sales. Furthermore, those firms exhibit significant home currency bias and international currency bias in borrowing: controlling for the geography of sales, they borrow more in their home currency and the two most traded currencies, the US dollar and the euro. We also show that the firms’ debt currency denomination choices are associated with export invoicing currency patterns in a way consistent with a currency hedging mechanism. In particular, firms domiciled in countries that invoice a larger share of their exports in either their home currency or in a vehicle currency exhibit a weaker connection between the currency denomination of their debt and the geography of their sales. Moreover, firms in countries that invoice more of their exports in an international currency are characterized by stronger international currency bias in debt issuance.
{"title":"Global sales, international currencies, and the currency denomination of debt","authors":"Riccardo Colacito , Yan Qian , Andreas Stathopoulos","doi":"10.1016/j.jfineco.2025.104184","DOIUrl":"10.1016/j.jfineco.2025.104184","url":null,"abstract":"<div><div>We document that the currency denomination of the debt of large firms in developed countries is strongly associated with the geographical distribution of their sales. Furthermore, those firms exhibit significant home currency bias and international currency bias in borrowing: controlling for the geography of sales, they borrow more in their home currency and the two most traded currencies, the US dollar and the euro. We also show that the firms’ debt currency denomination choices are associated with export invoicing currency patterns in a way consistent with a currency hedging mechanism. In particular, firms domiciled in countries that invoice a larger share of their exports in either their home currency or in a vehicle currency exhibit a weaker connection between the currency denomination of their debt and the geography of their sales. Moreover, firms in countries that invoice more of their exports in an international currency are characterized by stronger international currency bias in debt issuance.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104184"},"PeriodicalIF":10.4,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145322264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-11DOI: 10.1016/j.jfineco.2025.104183
Efraim Benmelech , Michał Zator
Using cross-country and German administrative data on robotization, we show that the impact of robots on firms and labor markets is limited. First, investment in robots is small and highly concentrated in a few industries, representing less than 0.3% of aggregate expenditures on equipment. Second, robotization does not grow as rapidly as Information Technology did in the past, and current growth is driven by gains in developing countries. Third, firms invest in robots when they face difficulties in finding workers and subsequently increase employment after the investment. The total employment effect in exposed industries and regions is negative but modest in magnitude. We discuss why the effects of robots are limited and demonstrate that other digital technologies have more potential for large economic impact.
{"title":"Robots and firm investment","authors":"Efraim Benmelech , Michał Zator","doi":"10.1016/j.jfineco.2025.104183","DOIUrl":"10.1016/j.jfineco.2025.104183","url":null,"abstract":"<div><div>Using cross-country and German administrative data on robotization, we show that the impact of robots on firms and labor markets is limited. First, investment in robots is small and highly concentrated in a few industries, representing less than 0.3% of aggregate expenditures on equipment. Second, robotization does not grow as rapidly as Information Technology did in the past, and current growth is driven by gains in developing countries. Third, firms invest in robots when they face difficulties in finding workers and subsequently increase employment after the investment. The total employment effect in exposed industries and regions is negative but modest in magnitude. We discuss why the effects of robots are limited and demonstrate that other digital technologies have more potential for large economic impact.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104183"},"PeriodicalIF":10.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-08DOI: 10.1016/j.jfineco.2025.104173
Lubos Pastor , Robert F. Stambaugh , Lucian A. Taylor
We estimate financial institutions’ portfolio tilts related to U.S. stocks’ environmental, social, and governance (ESG) characteristics. From 2012 to 2023, ESG-related tilts consistently total about 6% of the investment industry’s assets and rise from 17% to 27% of institutions’ total portfolio tilts. Significant ESG tilts arise from the choice of stocks held and, especially, the weights on stocks held. The largest institutions tilt increasingly toward green stocks, while other institutions and households tilt increasingly brown. Divestment from brown stocks is typically partial rather than full, even for individual mutual funds. UNPRI signatories and European institutions tilt greener; banks tilt browner.
{"title":"Green tilts","authors":"Lubos Pastor , Robert F. Stambaugh , Lucian A. Taylor","doi":"10.1016/j.jfineco.2025.104173","DOIUrl":"10.1016/j.jfineco.2025.104173","url":null,"abstract":"<div><div>We estimate financial institutions’ portfolio tilts related to U.S. stocks’ environmental, social, and governance (ESG) characteristics. From 2012 to 2023, ESG-related tilts consistently total about 6% of the investment industry’s assets and rise from 17% to 27% of institutions’ total portfolio tilts. Significant ESG tilts arise from the choice of stocks held and, especially, the weights on stocks held. The largest institutions tilt increasingly toward green stocks, while other institutions and households tilt increasingly brown. Divestment from brown stocks is typically partial rather than full, even for individual mutual funds. UNPRI signatories and European institutions tilt greener; banks tilt browner.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104173"},"PeriodicalIF":10.4,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1016/j.jfineco.2025.104170
Colleen Honigsberg , Edwin Hu , Robert J. Jackson Jr.
The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Prior empirical literature on financial advisors has largely focused on a single subset of financial advisors, but we create a database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC or state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator. This overlap has implications for labor allocation and market discipline. For example, of the individuals who exit FINRA’s broker regime, 79% were jointly registered in insurance upon exiting FINRA’s regime. This could be efficient if it reflects bad actors who transition to lower risk work, but our evidence shows that these advisors continue to engage in financial planning after they move to the insurance side, as over 90% maintain licenses to sell annuities. Moreover, those who committed misconduct when regulated by FINRA continue to have heightened levels of misconduct in insurance. Our findings have additional implications for regulatory discipline. In 2018 and 2019, FINRA proposed rules designed to nudge “bad” brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services—98% are currently registered with state regulators as insurance producers.
{"title":"Regulatory leakage among financial advisors: Evidence from FINRA regulation of “bad” brokers","authors":"Colleen Honigsberg , Edwin Hu , Robert J. Jackson Jr.","doi":"10.1016/j.jfineco.2025.104170","DOIUrl":"10.1016/j.jfineco.2025.104170","url":null,"abstract":"<div><div>The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Prior empirical literature on financial advisors has largely focused on a single subset of financial advisors, but we create a database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC or state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator. This overlap has implications for labor allocation and market discipline. For example, of the individuals who exit FINRA’s broker regime, 79% were jointly registered in insurance upon exiting FINRA’s regime. This could be efficient if it reflects bad actors who transition to lower risk work, but our evidence shows that these advisors continue to engage in financial planning after they move to the insurance side, as over 90% maintain licenses to sell annuities. Moreover, those who committed misconduct when regulated by FINRA continue to have heightened levels of misconduct in insurance. Our findings have additional implications for regulatory discipline. In 2018 and 2019, FINRA proposed rules designed to nudge “bad” brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services—98% are currently registered with state regulators as insurance producers.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104170"},"PeriodicalIF":10.4,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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