{"title":"From catch-up to frontier: The utility model as a learning device to escape the middle-income trap","authors":"Su Jung Jee, Kerstin Hötte","doi":"arxiv-2408.14205","DOIUrl":"https://doi.org/arxiv-2408.14205","url":null,"abstract":"Escaping the middle-income trap requires a country to develop indigenous\u0000technological capabilities for high value-added innovation. This study examines\u0000the role of second-tier patent systems, known as utility models (UMs), in\u0000promoting such capability acquisition in less developed countries. UMs are\u0000designed to incentivize incremental and adaptive innovation through lower\u0000novelty standards than patents, but their long-term impact on the capability\u0000acquisition process remains underexplored. Using South Korea as a case study\u0000and drawing on the characteristics of technological regimes in catching-up\u0000economies, we present three key findings: First, the country's post-catch-up\u0000frontier technologies (U.S. patents) are more impactful (highly cited) when\u0000they build on Korean domestic UMs. This suggests that UM-based imitative and\u0000adaptive learning laid the foundation for the country's globally competitive\u0000capabilities. Second, the impact of UM-based learning diminishes as the\u0000country's economy develops. Third, frontier technologies rooted in UMs\u0000contribute more to the country's own specialization than to follow-on\u0000innovations by foreign actors, compared to technologies without UM linkages. We\u0000discuss how technological regimes and industrial policies in catching-up\u0000economies interact with the UM system to bridge the catching-up (imitation- and\u0000adaptation-based) and post-catching-up (specialization- and creativity-based)\u0000phases.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192813","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}
{"title":"Import competition and domestic vertical integration: Theory and Evidence from Chinese firms","authors":"Xin Du, Xiaoxia Shi","doi":"arxiv-2408.13706","DOIUrl":"https://doi.org/arxiv-2408.13706","url":null,"abstract":"What impact does import competition have on firms' production organizational\u0000choices? Existing literature has predominantly focused on the relationship\u0000between import competition and firms' global production networks, with less\u0000attention given to domestic. We first develop a Nash-bargaining model to guide\u0000our empirical analysis, then utilize tariff changes as an exogenous shock to\u0000test our theoretical hypotheses using a database of Chinese listed firms from\u00002000 to 2023. Our findings indicate that a decrease in downstream tariffs lead\u0000to an increase in vertical integration. In our mechanism tests, we discover\u0000that a reduction in upstream tariffs also enhances this effect. Moreover, the\u0000impact of tariff reductions on vertical integration is primarily observed in\u0000industries with high asset specificity, indicating that asset-specificity is a\u0000crucial mechanism. We further explore whether import competition encourages\u0000vertical integration for technological acquisition purpose, the effect is found\u0000only among high-tech firms, while it's absent in non-high-tech firms. Our\u0000research provides new perspectives and evidence on how firms optimize their\u0000production organization in the process of globalization.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142193035","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}
{"title":"ESG Rating Disagreement and Corporate Total Factor Productivity:Inference and Prediction","authors":"Zhanli Li","doi":"arxiv-2408.13895","DOIUrl":"https://doi.org/arxiv-2408.13895","url":null,"abstract":"This paper explores the relationship between ESG rating disagreement and\u0000total factor productivity (TFP) based on data from Chinese domestic ESG rating\u0000agencies and financial data of A-share listed companies in China from 2015 to\u00002022. On one hand, the empirical results show that ESG rating disagreement\u0000reduces corporate TFP, a conclusion that is validated through multiple\u0000robustness tests. The mechanism analysis reveals an interaction effect between\u0000green innovation and ESG rating disagreement. Specifically, in firms without\u0000ESG rating disagreement, green innovation promotes the improvement of TFP;\u0000however, in firms with disagreement, although ESG rating disagreement may drive\u0000green innovation, this does not lead to an increase in TFP. Furthermore, ESG\u0000rating disagreement lower corporate TFP by increasing financing constraints.\u0000The heterogeneity analysis indicates that this effect is more pronounced in\u0000non-state-owned, asset-intensive, and low-pollution enterprises. On the other\u0000hand, XGBoost regression demonstrates that ESG rating disagreement play a\u0000significant role in predicting TFP, with SHAP values showing that the main\u0000effects are more evident in firms with larger ESG rating disagreement.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142193034","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}
Leonardo Matone, Ben Abramowitz, Nicholas Mattei, Avinash Balakrishnan
{"title":"DeepVoting: Learning Voting Rules with Tailored Embeddings","authors":"Leonardo Matone, Ben Abramowitz, Nicholas Mattei, Avinash Balakrishnan","doi":"arxiv-2408.13630","DOIUrl":"https://doi.org/arxiv-2408.13630","url":null,"abstract":"Aggregating the preferences of multiple agents into a collective decision is\u0000a common step in many important problems across areas of computer science\u0000including information retrieval, reinforcement learning, and recommender\u0000systems. As Social Choice Theory has shown, the problem of designing algorithms\u0000for aggregation rules with specific properties (axioms) can be difficult, or\u0000provably impossible in some cases. Instead of designing algorithms by hand, one\u0000can learn aggregation rules, particularly voting rules, from data. However, the\u0000prior work in this area has required extremely large models, or been limited by\u0000the choice of preference representation, i.e., embedding. We recast the problem\u0000of designing a good voting rule into one of learning probabilistic versions of\u0000voting rules that output distributions over a set of candidates. Specifically,\u0000we use neural networks to learn probabilistic social choice functions from the\u0000literature. We show that embeddings of preference profiles derived from the\u0000social choice literature allows us to learn existing voting rules more\u0000efficiently and scale to larger populations of voters more easily than other\u0000work if the embedding is tailored to the learning objective. Moreover, we show\u0000that rules learned using embeddings can be tweaked to create novel voting rules\u0000with improved axiomatic properties. Namely, we show that existing voting rules\u0000require only minor modification to combat a probabilistic version of the No\u0000Show Paradox.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192815","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}
{"title":"The Future of Work: Inequality, Artificial Intelligence, and What Can Be Done About It. A Literature Review","authors":"Caleb Peppiatt","doi":"arxiv-2408.13300","DOIUrl":"https://doi.org/arxiv-2408.13300","url":null,"abstract":"Generative Artificial Intelligence constitutes a new wave of automation.\u0000There is broad agreement among economists that humanity is potentially entering\u0000into a period of profound change. However, significant uncertainties and\u0000disagreements exist concerning a variety of overlapping topics: the share of\u0000jobs in which human labour is displaced and/or reinstated through automation;\u0000the effects on income inequality; the effects on job satisfaction; and,\u0000finally, what policy changes ought to be pursued to reduce potential negative\u0000impacts. This literature review seeks to clarify this landscape by mapping out\u0000key disagreements between positions, and to identify the critical elements upon\u0000which such disagreements rest. By surveying the current literature, the effects\u0000of AI on the future of work will be clarified.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192814","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}
{"title":"Understanding the Effect of Market Risks on New Pension System and Government Responsibility","authors":"Sourish Das, Bikramaditya Datta, Shiv Ratan Tiwari","doi":"arxiv-2408.13200","DOIUrl":"https://doi.org/arxiv-2408.13200","url":null,"abstract":"This study examines how market risks impact the sustainability and\u0000performance of the New Pension System (NPS). NPS relies on defined\u0000contributions from both employees and employers to build a corpus during the\u0000employee's service period. Upon retirement, employees use the corpus fund to\u0000sustain their livelihood. A critical concern for individuals is whether the\u0000corpus will grow sufficiently to be sustainable or if it will deplete, leaving\u0000them financially vulnerable at an advanced age. We explore the impact of market\u0000risks on the performance of the corpus resulting from the NPS. To address this,\u0000we quantify market risks using Monte Carlo simulations with historical data to\u0000model their impact on NPS. We quantify the risk of pension corpus being\u0000insufficient and the cost to the Government to hedge the risk arising from\u0000guaranteeing the pension.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192818","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}
{"title":"Education Opportunities for Rural Areas: Evidence from China's Higher Education Expansion","authors":"Ande Shen, Jiwei Zhou","doi":"arxiv-2408.12915","DOIUrl":"https://doi.org/arxiv-2408.12915","url":null,"abstract":"This paper explores the causal impact of education opportunities on rural\u0000areas by exploiting the higher education expansion (HEE) in China in 1999. By\u0000utilizing the detailed census data, the cohort-based difference-in-differences\u0000design indicates that the HEE increased college attendance and encouraged more\u0000people to attend senior high schools and that the effect is more significant in\u0000rural areas. Then we apply a similar approach to a novel panel data set of\u0000rural villages and households to examine the effect of education opportunities\u0000on rural areas. We find contrasting impacts on income and life quality between\u0000villages and households. Villages in provinces with higher HEE magnitudes\u0000underwent a drop in the average income and worse living facilities. On the\u0000contrary, households sending out migrants after the HEE experienced an increase\u0000in their per capita income. The phenomenon where villages experienced a ``brain\u0000drain'' and households with migrants gained after the HEE is explained by the\u0000fact that education could serve as a way to overcome the barrier of rural-urban\u0000migration. Our findings highlight the opposed impacts of education\u0000opportunities on rural development and household welfare in rural areas.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"143 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192817","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}
{"title":"Cross-border Commodity Pricing Strategy Optimization via Mixed Neural Network for Time Series Analysis","authors":"Lijuan Wang, Yijia Hu, Yan Zhou","doi":"arxiv-2408.12115","DOIUrl":"https://doi.org/arxiv-2408.12115","url":null,"abstract":"In the context of global trade, cross-border commodity pricing largely\u0000determines the competitiveness and market share of businesses. However,\u0000existing methodologies often prove inadequate, as they lack the agility and\u0000precision required to effectively respond to the dynamic international markets.\u0000Time series data is of great significance in commodity pricing and can reveal\u0000market dynamics and trends. Therefore, we propose a new method based on the\u0000hybrid neural network model CNN-BiGRU-SSA. The goal is to achieve accurate\u0000prediction and optimization of cross-border commodity pricing strategies\u0000through in-depth analysis and optimization of time series data. Our model\u0000undergoes experimental validation across multiple datasets. The results show\u0000that our method achieves significant performance advantages on datasets such as\u0000UNCTAD, IMF, WITS and China Customs. For example, on the UNCTAD dataset, our\u0000model reduces MAE to 4.357, RMSE to 5.406, and R2 to 0.961, significantly\u0000better than other models. On the IMF and WITS datasets, our method also\u0000achieves similar excellent performance. These experimental results verify the\u0000effectiveness and reliability of our model in the field of cross-border\u0000commodity pricing. Overall, this study provides an important reference for\u0000enterprises to formulate more reasonable and effective cross-border commodity\u0000pricing strategies, thereby enhancing market competitiveness and profitability.\u0000At the same time, our method also lays a foundation for the application of deep\u0000learning in the fields of international trade and economic strategy\u0000optimization, which has important theoretical and practical significance.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192825","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}
Su Jung Jee, Kerstin Hötte, Caoimhe Ring, Robert Burrell
{"title":"Making intellectual property rights work for climate technology transfer and innovation in developing countries","authors":"Su Jung Jee, Kerstin Hötte, Caoimhe Ring, Robert Burrell","doi":"arxiv-2408.12338","DOIUrl":"https://doi.org/arxiv-2408.12338","url":null,"abstract":"This study investigates the controversial role of Intellectual Property\u0000Rights (IPRs) in climate technology transfer and innovation in developing\u0000countries. Using a systematic literature review and expert interviews, we\u0000assess the role of IPRs on three sources of climate technology: (1)\u0000international technology transfer, (2) adaptive innovation, and (3) indigenous\u0000innovation. Our contributions are threefold. First, patents have limited impact\u0000in any of these channels, suggesting that current debates over IPRs may be\u0000directed towards the wrong targets. Second, trademarks and utility models\u0000provide incentives for climate innovation in the countries studied. Third,\u0000drawing from the results, we develop a framework to guide policy on how IPRs\u0000can work better in the broader context of climate and trade policies, outlining\u0000distinct mechanisms to support mitigation and adaptation. Our results indicate\u0000that market mechanisms, especially trade and demand-pull policies, should be\u0000prioritised for mitigation solutions. Adaptation differs, relying more on\u0000indigenous innovation due to local needs and low demand. Institutional\u0000mechanisms, such as finance and co-development, should be prioritised to build\u0000innovation capacities for adaptation.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192819","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}
{"title":"Empirical Equilibria in Agent-based Economic systems with Learning agents","authors":"Kshama Dwarakanath, Svitlana Vyetrenko, Tucker Balch","doi":"arxiv-2408.12038","DOIUrl":"https://doi.org/arxiv-2408.12038","url":null,"abstract":"We present an agent-based simulator for economic systems with heterogeneous\u0000households, firms, central bank, and government agents. These agents interact\u0000to define production, consumption, and monetary flow. Each agent type has\u0000distinct objectives, such as households seeking utility from consumption and\u0000the central bank targeting inflation and production. We define this multi-agent\u0000economic system using an OpenAI Gym-style environment, enabling agents to\u0000optimize their objectives through reinforcement learning. Standard multi-agent\u0000reinforcement learning (MARL) schemes, like independent learning, enable agents\u0000to learn concurrently but do not address whether the resulting strategies are\u0000at equilibrium. This study integrates the Policy Space Response Oracle (PSRO)\u0000algorithm, which has shown superior performance over independent MARL in games\u0000with homogeneous agents, with economic agent-based modeling. We use PSRO to\u0000develop agent policies approximating Nash equilibria of the empirical economic\u0000game, thereby linking to economic equilibria. Our results demonstrate that PSRO\u0000strategies achieve lower regret values than independent MARL strategies in our\u0000economic system with four agent types. This work aims to bridge artificial\u0000intelligence, economics, and empirical game theory towards future research.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192822","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}