The Intergovernmental Panel on Climate Change (IPCC) estimates that global net-zero should be achieved by 2050. To this end, many private firms are pledging to reach net-zero emissions by 2050. The Climate Data Steering Committee (CDSC) is working on an initiative to create a global central digital repository of climate disclosures, which aims to address the current data challenges. This paper assesses the progress within European financial institutions towards overcoming the data challenges outlined by the CDSC. Using a text-mining approach, coupled with the application of commercial Large Language Models (LLM) for context verification, we calculate a Greenhouse Gas Disclosure Index (GHGDI), by analysing 23 highly granular disclosures in the ESG reports between 2019 and 2021 of most of the significant banks under the ECB’s direct supervision. This index is then compared with the CDP score. The results indicate a moderate correlation between institutions not reporting to CDP upon request and a low GHGDI. Institutions with a high CDP score do not necessarily correlate with a high GHGDI.
{"title":"Assessing the data challenges of climate-related disclosures in european banks. A text mining study","authors":"Angel Ivan Moreno, Teresa Caminero","doi":"10.53479/33752","DOIUrl":"https://doi.org/10.53479/33752","url":null,"abstract":"The Intergovernmental Panel on Climate Change (IPCC) estimates that global net-zero should be achieved by 2050. To this end, many private firms are pledging to reach net-zero emissions by 2050. The Climate Data Steering Committee (CDSC) is working on an initiative to create a global central digital repository of climate disclosures, which aims to address the current data challenges. This paper assesses the progress within European financial institutions towards overcoming the data challenges outlined by the CDSC. Using a text-mining approach, coupled with the application of commercial Large Language Models (LLM) for context verification, we calculate a Greenhouse Gas Disclosure Index (GHGDI), by analysing 23 highly granular disclosures in the ESG reports between 2019 and 2021 of most of the significant banks under the ECB’s direct supervision. This index is then compared with the CDP score. The results indicate a moderate correlation between institutions not reporting to CDP upon request and a low GHGDI. Institutions with a high CDP score do not necessarily correlate with a high GHGDI.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"119 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139335749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of quantitative methods constitutes a standard component of the institutional investors’ portfolio management toolkit. In the last decade, several empirical studies have employed probabilistic or classification models to predict stock market excess returns, model bond ratings and default probabilities, as well as to forecast yield curves. To the authors’ knowledge, little research exists into their application to active fixed-income management. This paper contributes to filling this gap by comparing a machine learning algorithm, the Lasso logit regression, with a passive (buy-and-hold) investment strategy in the construction of a duration management model for high-grade bond portfolios, specifically focusing on US treasury bonds. Additionally, a two-step procedure is proposed, together with a simple ensemble averaging aimed at minimising the potential overfitting of traditional machine learning algorithms. A method to select thresholds that translate probabilities into signals based on conditional probability distributions is also introduced.
{"title":"Machine learning applied to active fixed-income portfolio management: a Lasso logit approach.","authors":"Mercedes de Luis, Emilio Rodríguez, Diego Torres","doi":"10.53479/33560","DOIUrl":"https://doi.org/10.53479/33560","url":null,"abstract":"The use of quantitative methods constitutes a standard component of the institutional investors’ portfolio management toolkit. In the last decade, several empirical studies have employed probabilistic or classification models to predict stock market excess returns, model bond ratings and default probabilities, as well as to forecast yield curves. To the authors’ knowledge, little research exists into their application to active fixed-income management. This paper contributes to filling this gap by comparing a machine learning algorithm, the Lasso logit regression, with a passive (buy-and-hold) investment strategy in the construction of a duration management model for high-grade bond portfolios, specifically focusing on US treasury bonds. Additionally, a two-step procedure is proposed, together with a simple ensemble averaging aimed at minimising the potential overfitting of traditional machine learning algorithms. A method to select thresholds that translate probabilities into signals based on conditional probability distributions is also introduced.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121288937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a contract-theoretic model in which banks choose pre-arranged and ex post funding to finance firms’ liquidity needs through credit lines. When liquidity needs are high, pre-arranged funding is key to sustaining lending and reducing the number of firms going into liquidation. Yet, in the presence of a pecuniary externality on firms’ liquidation values, competitive banks choose insufficient pre-funding compared with a constrained social planner. Constrained efficiency can be restored using regulatory liquidity ratios. The optimal regulatory ratio depends on the frequency of high liquidity need conditions, the value lost after a firm’s liquidation, and the premium on pre-funding.
{"title":"Optimal regulation of credit lines","authors":"J. E. Gutiérrez","doi":"10.53479/33492","DOIUrl":"https://doi.org/10.53479/33492","url":null,"abstract":"This paper presents a contract-theoretic model in which banks choose pre-arranged and ex post funding to finance firms’ liquidity needs through credit lines. When liquidity needs are high, pre-arranged funding is key to sustaining lending and reducing the number of firms going into liquidation. Yet, in the presence of a pecuniary externality on firms’ liquidation values, competitive banks choose insufficient pre-funding compared with a constrained social planner. Constrained efficiency can be restored using regulatory liquidity ratios. The optimal regulatory ratio depends on the frequency of high liquidity need conditions, the value lost after a firm’s liquidation, and the premium on pre-funding.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117335755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Central banks are increasingly using verbal communication for policymaking, focusing not only on traditional monetary policy, but also on a broad set of topics. One such topic is central bank digital currency (CBDC), which is attracting attention from the international community. The complex nature of this project means that it must be carefully designed to avoid unintended consequences, such as financial instability. We propose the use of different Natural Language Processing (NLP) techniques to better understand central banks’ stance towards CBDC, analyzing a set of central bank discourses from 2016 to 2022. We do this using traditional techniques, such as dictionary-based methods, and two large language models (LLMs), namely Bert and ChatGPT, concluding that LLMs better reflect the stance identified by human experts. In particular, we observe that ChatGPT exhibits a higher degree of alignment because it can capture subtler information than BERT. Our study suggests that LLMs are an effective tool to improve sentiment measurements for policy-specific texts, though they are not infallible and may be subject to new risks, like higher sensitivity to the length of texts, and prompt engineering.
{"title":"Analysis of CBDC Narrative OF Central Banks using Large Language Models","authors":"Andres Alonso-Robisco, Jose Manuel Carbo","doi":"10.53479/33412","DOIUrl":"https://doi.org/10.53479/33412","url":null,"abstract":"Central banks are increasingly using verbal communication for policymaking, focusing not only on traditional monetary policy, but also on a broad set of topics. One such topic is central bank digital currency (CBDC), which is attracting attention from the international community. The complex nature of this project means that it must be carefully designed to avoid unintended consequences, such as financial instability. We propose the use of different Natural Language Processing (NLP) techniques to better understand central banks’ stance towards CBDC, analyzing a set of central bank discourses from 2016 to 2022. We do this using traditional techniques, such as dictionary-based methods, and two large language models (LLMs), namely Bert and ChatGPT, concluding that LLMs better reflect the stance identified by human experts. In particular, we observe that ChatGPT exhibits a higher degree of alignment because it can capture subtler information than BERT. Our study suggests that LLMs are an effective tool to improve sentiment measurements for policy-specific texts, though they are not infallible and may be subject to new risks, like higher sensitivity to the length of texts, and prompt engineering.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127843681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan S. Mora-Sanguinetti, Laura Hospido, Andrés Atienza-Maeso
Las políticas públicas orientadas a lograr la igualdad de género, permitir una mayor conciliación de las actividades profesionales con la vida privada o luchar contra el acoso pueden tener consecuencias económicas; por ejemplo, a través de cambios en la oferta laboral de las mujeres u otros colectivos. Ahora bien, pese a que puede existir un aumento de la concienciación social sobre estos problemas, una cuestión diferente es si dicho aumento se ha sustanciado en medidas regulatorias concretas. Este documento tiene como objetivo cuantificar de manera exhaustiva cuándo, en qué lugares y a qué ritmo se han trasladado estas inquietudes sociales a la actividad regulatoria. El estudio abarca el período temporal 1996-2022, identificando normativa tanto estatal como para cada una de las Comunidades Autónomas (CCAA). El análisis, por tanto, organiza la información en formato panel. Los indicadores ponen de manifiesto la elevada heterogeneidad en lo que se refiere a la regulación de las distintas materias relacionadas. En lo relativo a los temas, es la normativa orientada a desarrollar políticas de no discriminación la más frecuente. En cuanto al ámbito territorial y administrativo, son Andalucía y Cataluña las CCAA en las que más normativa se ha aprobado. A modo de ejemplo de aplicación, se utiliza posteriormente la base de datos para entender la relación entre las normas aprobadas y determinados flujos de entrada en el mercado de trabajo para las mujeres. Nuestras estimaciones muestran una relación positiva entre el volumen de normas aprobadas en las materias de interés y los indicadores tanto de empleo como de participación laboral femenina.
{"title":"Los números de la regulación sobre igualdad. Cuantificación de la actividad normativa sobre no discriminación en España y su relación con las brechas de género en el mercado de trabajo.","authors":"Juan S. Mora-Sanguinetti, Laura Hospido, Andrés Atienza-Maeso","doi":"10.53479/33152","DOIUrl":"https://doi.org/10.53479/33152","url":null,"abstract":"Las políticas públicas orientadas a lograr la igualdad de género, permitir una mayor conciliación de las actividades profesionales con la vida privada o luchar contra el acoso pueden tener consecuencias económicas; por ejemplo, a través de cambios en la oferta laboral de las mujeres u otros colectivos. Ahora bien, pese a que puede existir un aumento de la concienciación social sobre estos problemas, una cuestión diferente es si dicho aumento se ha sustanciado en medidas regulatorias concretas.\u0000 Este documento tiene como objetivo cuantificar de manera exhaustiva cuándo, en qué lugares y a qué ritmo se han trasladado estas inquietudes sociales a la actividad regulatoria. El estudio abarca el período temporal 1996-2022, identificando normativa tanto estatal como para cada una de las Comunidades Autónomas (CCAA). El análisis, por tanto, organiza la información en formato panel. Los indicadores ponen de manifiesto la elevada heterogeneidad en lo que se refiere a la regulación de las distintas materias relacionadas. En lo relativo a los temas, es la normativa orientada a desarrollar políticas de no discriminación la más frecuente. En cuanto al ámbito territorial y administrativo, son Andalucía y Cataluña las CCAA en las que más normativa se ha aprobado.\u0000 A modo de ejemplo de aplicación, se utiliza posteriormente la base de datos para entender la relación entre las normas aprobadas y determinados flujos de entrada en el mercado de trabajo para las mujeres. Nuestras estimaciones muestran una relación positiva entre el volumen de normas aprobadas en las materias de interés y los indicadores tanto de empleo como de participación laboral femenina.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127228805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriel Jiménez, L. Laeven, David Martínez-Miera, J. Peydró
This paper shows that private incentives influence the allocation of public guaranteed lending (PGL), resulting in weaker banks shifting riskier corporate loans’ risk to taxpayers. We exploit data from the Banco de España’s Central Credit Register during the COVID-19 shock in Spain, and a stylized model is used to structure the empirical results. Unlike non-PGL, banks provide more PGL to riskier firms accounting for a higher share of their total lending to firms before the crisis. Importantly, the effects are stronger for weaker banks. Results using firm (bank) fixed effects and loan volume/price information suggest a supply-driven mechanism. Exploiting exogenous variations across similar firms with different access to PGL, we show that PGL increases banks’ lending to riskier firms, both overall and as a share of their total lending, especially for weaker banks.
{"title":"Public Guarantees and Private Banks’ Incentives: Evidence from the COVID-19 Crisis","authors":"Gabriel Jiménez, L. Laeven, David Martínez-Miera, J. Peydró","doi":"10.53479/30812","DOIUrl":"https://doi.org/10.53479/30812","url":null,"abstract":"This paper shows that private incentives influence the allocation of public guaranteed lending (PGL), resulting in weaker banks shifting riskier corporate loans’ risk to taxpayers. We exploit data from the Banco de España’s Central Credit Register during the COVID-19 shock in Spain, and a stylized model is used to structure the empirical results. Unlike non-PGL, banks provide more PGL to riskier firms accounting for a higher share of their total lending to firms before the crisis. Importantly, the effects are stronger for weaker banks. Results using firm (bank) fixed effects and loan volume/price information suggest a supply-driven mechanism. Exploiting exogenous variations across similar firms with different access to PGL, we show that PGL increases banks’ lending to riskier firms, both overall and as a share of their total lending, especially for weaker banks.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115673619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Longer life expectancy can affect individuals’ incentives to work, save and marry, net of any changes in their underlying health. We test this hypothesis by using the sudden arrival of a new treatment in 1995 that dramatically increased life expectancy for HIV-infected individuals. We compare the behavioural responses of HIV-infected individuals who were still in good health but who differed in their access to the new treatment. Those with access to treatment work substantially more, marry later, but do not save more. Our results highlight the importance of accounting for such incentive effects when valuing increases in life expectancy.
{"title":"When death was postponed: the effect of hiv medication on work, savings and marriage","authors":"M. Ejrnæs, Esteban García-Miralles, P. Lundborg","doi":"10.53479/30669","DOIUrl":"https://doi.org/10.53479/30669","url":null,"abstract":"Longer life expectancy can affect individuals’ incentives to work, save and marry, net of any changes in their underlying health. We test this hypothesis by using the sudden arrival of a new treatment in 1995 that dramatically increased life expectancy for HIV-infected individuals. We compare the behavioural responses of HIV-infected individuals who were still in good health but who differed in their access to the new treatment. Those with access to treatment work substantially more, marry later, but do not save more. Our results highlight the importance of accounting for such incentive effects when valuing increases in life expectancy.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132617802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alfredo García-Hiernaux, María T. González-Pérez, David E. Guerrero
This paper proposes a statistical model and a conceptual framework to estimate inflation volatility assuming rational inattention, where the decay in the level of attention reflects the arrival of news in the market. We estimate trend inflation and the conditional inflation volatility for Germany, Spain, the euro area and the United States using monthly data from January 2002 to March 2022 and test whether inflation was equal to or below 2% in this period in these regions. We decompose inflation volatility into positive and negative surprise components and characterise different inflation volatility scenarios during the Great Financial Crisis, the Sovereign Debt Crisis, and the post-COVID period. Our volatility measure outperforms the GARCH(1,1) model and the rolling standard deviation in one-step ahead volatility forecasts both in-sample and out-of-sample. The methodology proposed in this article is appropriate for estimating the conditional volatility of macro-financial variables. We recommend the inclusion of this measure in inflation dynamics monitoring and forecasting exercises.
{"title":"How to measure inFLAtion volatility. A note","authors":"Alfredo García-Hiernaux, María T. González-Pérez, David E. Guerrero","doi":"10.53479/30092","DOIUrl":"https://doi.org/10.53479/30092","url":null,"abstract":"This paper proposes a statistical model and a conceptual framework to estimate inflation volatility assuming rational inattention, where the decay in the level of attention reflects the arrival of news in the market. We estimate trend inflation and the conditional inflation volatility for Germany, Spain, the euro area and the United States using monthly data from January 2002 to March 2022 and test whether inflation was equal to or below 2% in this period in these regions. We decompose inflation volatility into positive and negative surprise components and characterise different inflation volatility scenarios during the Great Financial Crisis, the Sovereign Debt Crisis, and the post-COVID period. Our volatility measure outperforms the GARCH(1,1) model and the rolling standard deviation in one-step ahead volatility forecasts both in-sample and out-of-sample. The methodology proposed in this article is appropriate for estimating the conditional volatility of macro-financial variables. We recommend the inclusion of this measure in inflation dynamics monitoring and forecasting exercises.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128962601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan S. Mora-Sanguinetti, J. Quintana, Isabel Soler, R. Spruk
This paper studies for the first time the impact on various measures of economic efficiency of regulatory complexity by sector in Spain. We base our analysis on an innovative database that classifies 206,777 regulations by economic sector and region, which highlights the growing volume of regulation, as well as its diversity by sector, region and business cycle stage. This analysis first looks at the aggregate impacts of sectoral regulatory complexity on the employment-to-population ratio, total working hours, sectoral GDP shares, labour intensity and capital intensity. Secondly it delves into the heterogeneous impacts observed across firms of different sizes and ages, drawing on the MCVL (Continuous Work History Sample), a rich database at the enterprise level. On the first front, we estimate a set of multiple fixed-effects model specifications across 13 economic sectors, 23 regulatory sectors and 17 Spanish regions over the period 1995-2020. Our results suggest that greater regulatory complexity has a negative impact on the employment rate and on value added. The effect on employment is consistent with previous findings for the United States. In particular, ceteris paribus, each additional increase in the regulatory complexity index is associated with a 0.7 percent drop in the sector-level employment share. Furthermore, our findings suggest that several distortionary sector-level effects of increasing regulatory complexity are taking place. For instance, markedly lower labour intensity and decreased sector-level investment rates, which confirm that greater regulatory complexity entails non-trivial sector-level costs. Distortionary effects of regulatory complexity materialise through compositional differences, mainly in the form of reduced wages and a lower investment rate.
{"title":"Sector-level economic effects of regulatory complexity: evidence from Spain","authors":"Juan S. Mora-Sanguinetti, J. Quintana, Isabel Soler, R. Spruk","doi":"10.53479/29854","DOIUrl":"https://doi.org/10.53479/29854","url":null,"abstract":"This paper studies for the first time the impact on various measures of economic efficiency of regulatory complexity by sector in Spain. We base our analysis on an innovative database that classifies 206,777 regulations by economic sector and region, which highlights the growing volume of regulation, as well as its diversity by sector, region and business cycle stage.\u0000 This analysis first looks at the aggregate impacts of sectoral regulatory complexity on the employment-to-population ratio, total working hours, sectoral GDP shares, labour intensity and capital intensity. Secondly it delves into the heterogeneous impacts observed across firms of different sizes and ages, drawing on the MCVL (Continuous Work History Sample), a rich database at the enterprise level. \u0000 On the first front, we estimate a set of multiple fixed-effects model specifications across 13 economic sectors, 23 regulatory sectors and 17 Spanish regions over the period 1995-2020. Our results suggest that greater regulatory complexity has a negative impact on the employment rate and on value added. The effect on employment is consistent with previous findings for the United States. In particular, ceteris paribus, each additional increase in the regulatory complexity index is associated with a 0.7 percent drop in the sector-level employment share. Furthermore, our findings suggest that several distortionary sector-level effects of increasing regulatory complexity are taking place. For instance, markedly lower labour intensity and decreased sector-level investment rates, which confirm that greater regulatory complexity entails non-trivial sector-level costs. Distortionary effects of regulatory complexity materialise through compositional differences, mainly in the form of reduced wages and a lower investment rate.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131690800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aggregate and sectoral effects of public investment crucially depend on the interaction between the output elasticity to public capital and input-output linkages. We identify this dependence through the lens of a New Keynesian production network. This setting doubles the socially optimal amount of public capital relative to the average one-sector economy, leading to a substantial amplification of the public investment multiplier. We also document novel sectoral implications of public investment. Although public investment is concentrated in far fewer sectors than public consumption, its effects are relatively more evenly distributed across industries. We validate this model implication in the data.
{"title":"The public investment multiplier in a production network","authors":"Alessandro Peri, Omar Rachedi, Iacopo Varotto","doi":"10.53479/29825","DOIUrl":"https://doi.org/10.53479/29825","url":null,"abstract":"Aggregate and sectoral effects of public investment crucially depend on the interaction between the output elasticity to public capital and input-output linkages. We identify this dependence through the lens of a New Keynesian production network. This setting doubles the socially optimal amount of public capital relative to the average one-sector economy, leading to a substantial amplification of the public investment multiplier. We also document novel sectoral implications of public investment. Although public investment is concentrated in far fewer sectors than public consumption, its effects are relatively more evenly distributed across industries. We validate this model implication in the data.","PeriodicalId":296461,"journal":{"name":"Documentos de Trabajo","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122165965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：