Regional differences in carbon emission efficiency arise from disparities in resource distribution, industrial structure, and development level, which are often influenced by government policy preferences. However, currently, most studies fail to consider the impact of government policy preferences and data uncertainty on carbon emission efficiency. To address the above limitations, this study proposes a hybrid model based on $delta$-slack-based model ($delta$-SBM) and ordinal priority approach (OPA) for measuring carbon emission efficiency driven by government policy preferences under data uncertainty. The proposed $delta$-SBM-OPA model incorporates constraints on the importance of input and output variables under different policy preference scenarios. It then develops the efficiency optimization model with Farrell frontiers and efficiency tapes to deal with the data uncertainty in input and output variables. This study demonstrates the proposed model by analyzing industrial carbon emission efficiency of Chinese provinces in 2021. It examines the carbon emission efficiency and corresponding clustering results of provinces under three types of policies: economic priority, environmental priority, and technological priority, with varying priority preferences. The results indicate that the carbon emission efficiency of the 30 provinces can mainly be categorized into technology-driven, development-balanced, and transition-potential types, with most provinces achieving optimal efficiency under the technology-dominant preferences across all policy scenarios. Ultimately, this study suggests a tailored roadmap and crucial initiatives for different provinces to progressively and systematically work towards achieving the low carbon goal.
{"title":"A Novel $δ$-SBM-OPA Approach for Policy-Driven Analysis of Carbon Emission Efficiency under Uncertainty in the Chinese Industrial Sector","authors":"Shutian Cui, Renlong Wang, Xiaoyan Li","doi":"arxiv-2408.11600","DOIUrl":"https://doi.org/arxiv-2408.11600","url":null,"abstract":"Regional differences in carbon emission efficiency arise from disparities in\u0000resource distribution, industrial structure, and development level, which are\u0000often influenced by government policy preferences. However, currently, most\u0000studies fail to consider the impact of government policy preferences and data\u0000uncertainty on carbon emission efficiency. To address the above limitations,\u0000this study proposes a hybrid model based on $delta$-slack-based model\u0000($delta$-SBM) and ordinal priority approach (OPA) for measuring carbon\u0000emission efficiency driven by government policy preferences under data\u0000uncertainty. The proposed $delta$-SBM-OPA model incorporates constraints on\u0000the importance of input and output variables under different policy preference\u0000scenarios. It then develops the efficiency optimization model with Farrell\u0000frontiers and efficiency tapes to deal with the data uncertainty in input and\u0000output variables. This study demonstrates the proposed model by analyzing\u0000industrial carbon emission efficiency of Chinese provinces in 2021. It examines\u0000the carbon emission efficiency and corresponding clustering results of\u0000provinces under three types of policies: economic priority, environmental\u0000priority, and technological priority, with varying priority preferences. The\u0000results indicate that the carbon emission efficiency of the 30 provinces can\u0000mainly be categorized into technology-driven, development-balanced, and\u0000transition-potential types, with most provinces achieving optimal efficiency\u0000under the technology-dominant preferences across all policy scenarios.\u0000Ultimately, this study suggests a tailored roadmap and crucial initiatives for\u0000different provinces to progressively and systematically work towards achieving\u0000the low carbon goal.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192821","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 reinforcement learning algorithms in financial trading is becoming increasingly prevalent. However, the autonomous nature of these algorithms can lead to unexpected outcomes that deviate from traditional game-theoretical predictions and may even destabilize markets. In this study, we examine a scenario in which two autonomous agents, modeled with Double Deep Q-Learning, learn to liquidate the same asset optimally in the presence of market impact, using the Almgren-Chriss (2000) framework. Our results show that the strategies learned by the agents deviate significantly from the Nash equilibrium of the corresponding market impact game. Notably, the learned strategies exhibit tacit collusion, closely aligning with the Pareto-optimal solution. We further explore how different levels of market volatility influence the agents' performance and the equilibria they discover, including scenarios where volatility differs between the training and testing phases.
{"title":"Deviations from the Nash equilibrium and emergence of tacit collusion in a two-player optimal execution game with reinforcement learning","authors":"Fabrizio Lillo, Andrea Macrì","doi":"arxiv-2408.11773","DOIUrl":"https://doi.org/arxiv-2408.11773","url":null,"abstract":"The use of reinforcement learning algorithms in financial trading is becoming\u0000increasingly prevalent. However, the autonomous nature of these algorithms can\u0000lead to unexpected outcomes that deviate from traditional game-theoretical\u0000predictions and may even destabilize markets. In this study, we examine a\u0000scenario in which two autonomous agents, modeled with Double Deep Q-Learning,\u0000learn to liquidate the same asset optimally in the presence of market impact,\u0000using the Almgren-Chriss (2000) framework. Our results show that the strategies\u0000learned by the agents deviate significantly from the Nash equilibrium of the\u0000corresponding market impact game. Notably, the learned strategies exhibit tacit\u0000collusion, closely aligning with the Pareto-optimal solution. We further\u0000explore how different levels of market volatility influence the agents'\u0000performance and the equilibria they discover, including scenarios where\u0000volatility differs between the training and testing phases.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"143 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192829","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 investigates the value of recommendations for disseminating economic information, with a focus on frictions resulting from preference heterogeneity. We consider Bayesian expected-payoff maximizers who receive non-strategic recommendations by other consumers. The paper provides conditions under which different consumer types accept these recommendations. Moreover, we assess the overall value of a recommendation system and the determinants of that value. Our analysis highlights the importance of disentangling objective information from subjective preferences when designing value-maximizing recommendation systems.
{"title":"A Theory of Recommendations","authors":"Jean-Michel Benkert, Armin Schmutzler","doi":"arxiv-2408.11362","DOIUrl":"https://doi.org/arxiv-2408.11362","url":null,"abstract":"This paper investigates the value of recommendations for disseminating\u0000economic information, with a focus on frictions resulting from preference\u0000heterogeneity. We consider Bayesian expected-payoff maximizers who receive\u0000non-strategic recommendations by other consumers. The paper provides conditions\u0000under which different consumer types accept these recommendations. Moreover, we\u0000assess the overall value of a recommendation system and the determinants of\u0000that value. Our analysis highlights the importance of disentangling objective\u0000information from subjective preferences when designing value-maximizing\u0000recommendation systems.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192823","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}
Each household in a population characterized by income heterogeneity faces random demand for electricity and decides if and when it should adopt a solar product, rooftop solar or community solar. A central planner, aiming to meet an adoption level target within a set time, offers net metering and subsidy on solar products and minimizes its total cost. Our focus is on analyzing the interactions of three new features we add to the literature: income diversity, availability of community solar, and consideration of adoption timing. {Methodology and results:} We develop a bilevel optimization formulation to derive the optimal subsidy policy. The upper level (planner's) problem is a constrained non-linear optimization model in which the planner aims to minimize the average subsidy cost. The lower level (household's) problem is an optimal stopping formulation, which captures the adoption decisions of the households. We derive a closed-form expression for the distribution of optimal adoption time of households for a given subsidy policy. We show that the planner's problem is convex in the case of homogeneous subsidy for the two products. {Managerial implications:} Our results underscore the importance for planners to consider three factors - adoption level target, time target, and subsidy budget - simultaneously as they work in tandem to influence the adoption outcome. The planners must also consider the inclusion of community solar in their plans because, as we show, community and rooftop solar attract households from different sides of the income spectrum. In the presence of income inequality, the availability of community makes it easier to meet solar adoption targets.
{"title":"Rooftop and Community Solar Adoption with Income Heterogeneity","authors":"Swapnil Rayal, Apurva Jain, Matthew Lorig","doi":"arxiv-2408.11970","DOIUrl":"https://doi.org/arxiv-2408.11970","url":null,"abstract":"Each household in a population characterized by income heterogeneity faces\u0000random demand for electricity and decides if and when it should adopt a solar\u0000product, rooftop solar or community solar. A central planner, aiming to meet an\u0000adoption level target within a set time, offers net metering and subsidy on\u0000solar products and minimizes its total cost. Our focus is on analyzing the\u0000interactions of three new features we add to the literature: income diversity,\u0000availability of community solar, and consideration of adoption timing.\u0000{Methodology and results:} We develop a bilevel optimization formulation to\u0000derive the optimal subsidy policy. The upper level (planner's) problem is a\u0000constrained non-linear optimization model in which the planner aims to minimize\u0000the average subsidy cost. The lower level (household's) problem is an optimal\u0000stopping formulation, which captures the adoption decisions of the households.\u0000We derive a closed-form expression for the distribution of optimal adoption\u0000time of households for a given subsidy policy. We show that the planner's\u0000problem is convex in the case of homogeneous subsidy for the two products.\u0000{Managerial implications:} Our results underscore the importance for planners\u0000to consider three factors - adoption level target, time target, and subsidy\u0000budget - simultaneously as they work in tandem to influence the adoption\u0000outcome. The planners must also consider the inclusion of community solar in\u0000their plans because, as we show, community and rooftop solar attract households\u0000from different sides of the income spectrum. In the presence of income\u0000inequality, the availability of community makes it easier to meet solar\u0000adoption targets.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192820","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}
Dimitar Kitanovski, Igor Mishkovski, Viktor Stojkoski, Miroslav Mirchev
Maintaining a balance between returns and volatility is a common strategy for portfolio diversification, whether investing in traditional equities or digital assets like cryptocurrencies. One approach for diversification is the application of community detection or clustering, using a network representing the relationships between assets. We examine two network representations, one based on a standard distance matrix based on correlation, and another based on mutual information. The Louvain and Affinity propagation algorithms were employed for finding the network communities (clusters) based on annual data. Furthermore, we examine building assets' co-occurrence networks, where communities are detected for each month throughout a whole year and then the links represent how often assets belong to the same community. Portfolios are then constructed by selecting several assets from each community based on local properties (degree centrality), global properties (closeness centrality), or explained variance (Principal component analysis), with three value ranges (max, med, min), calculated on a maximal spanning tree or a fully connected community sub-graph. We explored these various strategies on data from the S&P 500 and the Top 203 cryptocurrencies with a market cap above 2M USD in the period from Jan 2019 to Sep 2022. Moreover, we study into more details the periods of the beginning of the COVID-19 outbreak and the start of the war in Ukraine. The results confirm some of the previous findings already known for traditional stock markets and provide some further insights, while they reveal an opposing trend in the crypto-assets market.
{"title":"Network-based diversification of stock and cryptocurrency portfolios","authors":"Dimitar Kitanovski, Igor Mishkovski, Viktor Stojkoski, Miroslav Mirchev","doi":"arxiv-2408.11739","DOIUrl":"https://doi.org/arxiv-2408.11739","url":null,"abstract":"Maintaining a balance between returns and volatility is a common strategy for\u0000portfolio diversification, whether investing in traditional equities or digital\u0000assets like cryptocurrencies. One approach for diversification is the\u0000application of community detection or clustering, using a network representing\u0000the relationships between assets. We examine two network representations, one\u0000based on a standard distance matrix based on correlation, and another based on\u0000mutual information. The Louvain and Affinity propagation algorithms were\u0000employed for finding the network communities (clusters) based on annual data.\u0000Furthermore, we examine building assets' co-occurrence networks, where\u0000communities are detected for each month throughout a whole year and then the\u0000links represent how often assets belong to the same community. Portfolios are\u0000then constructed by selecting several assets from each community based on local\u0000properties (degree centrality), global properties (closeness centrality), or\u0000explained variance (Principal component analysis), with three value ranges\u0000(max, med, min), calculated on a maximal spanning tree or a fully connected\u0000community sub-graph. We explored these various strategies on data from the S&P\u0000500 and the Top 203 cryptocurrencies with a market cap above 2M USD in the\u0000period from Jan 2019 to Sep 2022. Moreover, we study into more details the\u0000periods of the beginning of the COVID-19 outbreak and the start of the war in\u0000Ukraine. The results confirm some of the previous findings already known for\u0000traditional stock markets and provide some further insights, while they reveal\u0000an opposing trend in the crypto-assets market.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192826","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}
We investigate the emergence of Deep Learning as a technoscientific field, emphasizing the role of open labeled datasets. Through qualitative and quantitative analyses, we evaluate the role of datasets like CIFAR-10 in advancing computer vision and object recognition, which are central to the Deep Learning revolution. Our findings highlight CIFAR-10's crucial role and enduring influence on the field, as well as its importance in teaching ML techniques. Results also indicate that dataset characteristics such as size, number of instances, and number of categories, were key factors. Econometric analysis confirms that CIFAR-10, a small-but-sufficiently-large open dataset, played a significant and lasting role in technological advancements and had a major function in the development of the early scientific literature as shown by citation metrics.
我们研究了深度学习作为一个技术科学领域的兴起，强调了开放标签数据集的作用。通过定性和定量分析，我们评估了 CIFAR-10 等数据集在推动计算机视觉和物体识别方面的作用，而计算机视觉和物体识别是深度学习革命的核心。我们的研究结果凸显了 CIFAR-10 在该领域的关键作用和持久影响力，以及它在 ML 技术教学中的重要性。结果还表明，数据集的特征（如大小、实例数量和类别数量）是关键因素。计量经济学分析证实，CIFAR-10 是一个规模虽小但足够大的开放数据集，它在技术进步中发挥了重要而持久的作用，并在早期科学文献的发展中发挥了重要作用，这一点可以通过引用指标来证明。
{"title":"How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning","authors":"Daniel Souza, Aldo Geuna, Jeff Rodríguez","doi":"arxiv-2408.10359","DOIUrl":"https://doi.org/arxiv-2408.10359","url":null,"abstract":"We investigate the emergence of Deep Learning as a technoscientific field,\u0000emphasizing the role of open labeled datasets. Through qualitative and\u0000quantitative analyses, we evaluate the role of datasets like CIFAR-10 in\u0000advancing computer vision and object recognition, which are central to the Deep\u0000Learning revolution. Our findings highlight CIFAR-10's crucial role and\u0000enduring influence on the field, as well as its importance in teaching ML\u0000techniques. Results also indicate that dataset characteristics such as size,\u0000number of instances, and number of categories, were key factors. Econometric\u0000analysis confirms that CIFAR-10, a small-but-sufficiently-large open dataset,\u0000played a significant and lasting role in technological advancements and had a\u0000major function in the development of the early scientific literature as shown\u0000by citation metrics.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192824","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}
There has been a growing interest in multi-agent simulators in the domain of economic modeling. However, contemporary research often involves developing reinforcement learning (RL) based models that focus solely on a single type of agents, such as households, firms, or the government. Such an approach overlooks the adaptation of interacting agents thereby failing to capture the complexity of real-world economic systems. In this work, we consider a multi-agent simulator comprised of RL agents of numerous types, including heterogeneous households, firm, central bank and government. In particular, we focus on the crucial role of the government in distributing tax credits to households. We conduct two broad categories of comprehensive experiments dealing with the impact of tax credits on 1) households with varied degrees of myopia (short-sightedness in spending and saving decisions), and 2) households with diverse liquidity profiles. The first category of experiments examines the impact of the frequency of tax credits (e.g. annual vs quarterly) on consumption patterns of myopic households. The second category of experiments focuses on the impact of varying tax credit distribution strategies on households with differing liquidities. We validate our simulation model by reproducing trends observed in real households upon receipt of unforeseen, uniform tax credits, as documented in a JPMorgan Chase report. Based on the results of the latter, we propose an innovative tax credit distribution strategy for the government to reduce inequality among households. We demonstrate the efficacy of this strategy in improving social welfare in our simulation results.
{"title":"Tax Credits and Household Behavior: The Roles of Myopic Decision-Making and Liquidity in a Simulated Economy","authors":"Jialin Dong, Kshama Dwarakanath, Svitlana Vyetrenko","doi":"arxiv-2408.10391","DOIUrl":"https://doi.org/arxiv-2408.10391","url":null,"abstract":"There has been a growing interest in multi-agent simulators in the domain of\u0000economic modeling. However, contemporary research often involves developing\u0000reinforcement learning (RL) based models that focus solely on a single type of\u0000agents, such as households, firms, or the government. Such an approach\u0000overlooks the adaptation of interacting agents thereby failing to capture the\u0000complexity of real-world economic systems. In this work, we consider a\u0000multi-agent simulator comprised of RL agents of numerous types, including\u0000heterogeneous households, firm, central bank and government. In particular, we\u0000focus on the crucial role of the government in distributing tax credits to\u0000households. We conduct two broad categories of comprehensive experiments\u0000dealing with the impact of tax credits on 1) households with varied degrees of\u0000myopia (short-sightedness in spending and saving decisions), and 2) households\u0000with diverse liquidity profiles. The first category of experiments examines the\u0000impact of the frequency of tax credits (e.g. annual vs quarterly) on\u0000consumption patterns of myopic households. The second category of experiments\u0000focuses on the impact of varying tax credit distribution strategies on\u0000households with differing liquidities. We validate our simulation model by\u0000reproducing trends observed in real households upon receipt of unforeseen,\u0000uniform tax credits, as documented in a JPMorgan Chase report. Based on the\u0000results of the latter, we propose an innovative tax credit distribution\u0000strategy for the government to reduce inequality among households. We\u0000demonstrate the efficacy of this strategy in improving social welfare in our\u0000simulation results.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192831","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}
Water market is a contemporary marketplace for water trading and is deemed to one of the most efficient instruments to improve the social welfare. In modern water markets, the two widely used trading systems are an improved pair-wise trading, and a 'smart market' or common pool method. In comparison with the economic model, this paper constructs a conceptual mathematic model through the HARA utility functions. Mirroring the concepts such as Nash Equilibrium, Pareto optimal and stable matching in economy, three significant propositions are acquired which illustrate the advantages of the common pool method compared with the improved pair-wise trading.
{"title":"The Economic Analysis of the Common Pool Method through the HARA Utility Functions","authors":"Mu Lin, Di Zhang, Ben Chen, Hang Zheng","doi":"arxiv-2408.05194","DOIUrl":"https://doi.org/arxiv-2408.05194","url":null,"abstract":"Water market is a contemporary marketplace for water trading and is deemed to\u0000one of the most efficient instruments to improve the social welfare. In modern\u0000water markets, the two widely used trading systems are an improved pair-wise\u0000trading, and a 'smart market' or common pool method. In comparison with the\u0000economic model, this paper constructs a conceptual mathematic model through the\u0000HARA utility functions. Mirroring the concepts such as Nash Equilibrium, Pareto\u0000optimal and stable matching in economy, three significant propositions are\u0000acquired which illustrate the advantages of the common pool method compared\u0000with the improved pair-wise trading.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"136 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141943480","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}
A large body of literature in economics and political science examines the impact of democracy and political freedoms on various outcomes using cross-country comparisons. This paper explores the possibility that any positive impact of democracy observed in these studies might be attributed to powerful democratic nations, their allies, and international organizations treating democracies more favorably than nondemocracies, a concept I refer to as democratic favor channel. Firstly, after I control for being targeted by sanctions from G7 or the United Nations and having military confrontations and cooperation with the West, most of the positive effects of democracy on growth in cross-country panel regressions become insignificant or negatively significant. Secondly, using the same empirical specification as this literature for demonstrating intermediating forces, I show that getting sanctioned, militarily attacked, and not having defense cooperation with the West are plausible channels through which democracy causes growth. Lastly, in the pre-Soviet-collapse period, which coincides with the time when democracy promotion was less often used as a justification for sanctions, the impact of democracy on GDP per capita is already weak or negative without any additional controls, and it becomes further negative once democratic favor is controlled. These findings support the democratic favor channel and challenge the idea that the institutional qualities of democracy per se lead to desirable outcomes. The critique provided in this paper applies to the broader comparative institutions literature in social sciences and political philosophy.
经济学和政治学中有大量文献通过跨国比较研究了民主和政治自由对各种结果的影响。本文探讨了这样一种可能性，即在这些研究中观察到的民主的积极影响可能归因于强大的民主国家、其盟国和国际组织给予民主国家比非民主国家更优惠的待遇，我将这一概念称为民主优惠渠道。首先，在控制了被七国集团或联合国制裁以及与西方国家发生军事冲突和合作之后，在跨国面板回归中，民主对经济增长的正向影响大多变得不显著或负向显著。其次，我使用了与上述文献相同的经验规格来证明中介力量，结果表明，获得制裁、受到军事攻击以及与西方国家没有防务合作都是民主导致增长的合理渠道。最后，在苏联解体前的时期，也就是促进民主较少被用作制裁理由的时期，民主对人均 GDP 的影响在没有任何额外控制的情况下已经很弱或为负，而一旦控制了民主支持，这种影响就会进一步变为负值。这些发现支持了民主支持渠道，并对民主的制度品质本身会带来理想结果的观点提出了质疑。本文的批判适用于社会科学和政治哲学中更广泛的比较制度文献。
{"title":"Democratic Favor Channel","authors":"Ziho Park","doi":"arxiv-2408.05059","DOIUrl":"https://doi.org/arxiv-2408.05059","url":null,"abstract":"A large body of literature in economics and political science examines the\u0000impact of democracy and political freedoms on various outcomes using\u0000cross-country comparisons. This paper explores the possibility that any\u0000positive impact of democracy observed in these studies might be attributed to\u0000powerful democratic nations, their allies, and international organizations\u0000treating democracies more favorably than nondemocracies, a concept I refer to\u0000as democratic favor channel. Firstly, after I control for being targeted by\u0000sanctions from G7 or the United Nations and having military confrontations and\u0000cooperation with the West, most of the positive effects of democracy on growth\u0000in cross-country panel regressions become insignificant or negatively\u0000significant. Secondly, using the same empirical specification as this\u0000literature for demonstrating intermediating forces, I show that getting\u0000sanctioned, militarily attacked, and not having defense cooperation with the\u0000West are plausible channels through which democracy causes growth. Lastly, in\u0000the pre-Soviet-collapse period, which coincides with the time when democracy\u0000promotion was less often used as a justification for sanctions, the impact of\u0000democracy on GDP per capita is already weak or negative without any additional\u0000controls, and it becomes further negative once democratic favor is controlled.\u0000These findings support the democratic favor channel and challenge the idea that\u0000the institutional qualities of democracy per se lead to desirable outcomes. The\u0000critique provided in this paper applies to the broader comparative institutions\u0000literature in social sciences and political philosophy.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141943475","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}
Erik-Benjamin Börschlein, Mario Bossler, Martin Popp
Labor market tightness tremendously increased in Germany between 2012 and 2022. We analyze the effect of tightness on wages by combining social security data with unusually rich information on vacancies and job seekers. Instrumental variable regressions reveal positive elasticities between 0.004 and 0.011, implying that higher tightness explains between 7 and 19 percent of the real wage increase. We report greater elasticities for new hires, high-skilled workers, the Eastern German labor market, and the service sector. In particular, tightness raised wages at the bottom of the wage distribution, contributing to the decline in wage inequality over the last decade.
{"title":"Scarce Workers, High Wages?","authors":"Erik-Benjamin Börschlein, Mario Bossler, Martin Popp","doi":"arxiv-2408.04508","DOIUrl":"https://doi.org/arxiv-2408.04508","url":null,"abstract":"Labor market tightness tremendously increased in Germany between 2012 and\u00002022. We analyze the effect of tightness on wages by combining social security\u0000data with unusually rich information on vacancies and job seekers. Instrumental\u0000variable regressions reveal positive elasticities between 0.004 and 0.011,\u0000implying that higher tightness explains between 7 and 19 percent of the real\u0000wage increase. We report greater elasticities for new hires, high-skilled\u0000workers, the Eastern German labor market, and the service sector. In\u0000particular, tightness raised wages at the bottom of the wage distribution,\u0000contributing to the decline in wage inequality over the last decade.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141943477","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}
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