ABSTRACT This paper characterizes higher‐order Ross more risk aversion by means of risk compensation rather than the traditional risk premium. Our approach extends the willingness‐to‐accept (WTA) framework of Denuit and Eeckhoudt (2013) to a broader class of risk changes. In addition, we provide a characterization of the strength of precautionary saving based on precautionary compensation, thereby complementing the analysis of Liu (2014), which is based on the precautionary premium.
ABSTRACT The primary focus of this essay is to obtain new estimates of the price sensitivity of cigarette consumption and related outcomes using the 1979 cohort of the National Longitudinal Survey of Youth (NLSY79). This work expands on the existing literature on the topic by taking into account measures of time preference in the NLSY79 to examine interactions between these measures and price in the demand function for cigarettes. My specific hypothesis is that those who discount the future consequences of their current actions heavily are likely to be more sensitive to price than those who do not. I find that the people who discount the future heavily are more sensitive to price change.
This paper examines how the financial development of the target economy evolves under the long-lasting economic sanctions, emphasizing the temporal patterns of the impact. Using panel data for 136 economies from 1980 to 2021 and an event-study approach, we identified a temporal pattern that illustrates how economic sanctions exert a significant negative impact on financial development, progressing step by step from the market to the institutional level. These patterns are especially evident in the asymmetric effects between financial markets and institutions. Financial markets exhibit earlier and short-lived reactions, characterized by rapid responses to external shocks driven by investor expectations. In contrast, financial institutions display delayed responses, with long-term effects shaped by risk-buffering and restructuring mechanisms. We have illustrated a multi-stage transmission process. Initially, economic sanctions trigger market disruptions. This is followed by institutions reallocating resources to maximize profit/efficiency, which reshapes the financial system over time.
ABSTRACT The study of market efficiency is one of the most covered topics in the field of financial markets, with the Efficient Market Hypothesis gathering devotees as well as several critics. The perception of markets as agents with an adaptive nature gave rise to the Adaptive Market Hypothesis (AMH). This paper aims to combine this evolutionary view of market efficiency with the need to assess the behavior of emerging markets over the years. The empirical method selected was the Adjusted Market Inefficiency Magnitude. The sample consists of daily returns between 2005 and 2023 for six stock indices, namely the Indian (BSESN), Brazilian (BVSP), Chinese (CSI300), South African (JALSH), South Korean (KS11), and Taiwanese (TWII), representing the emerging economies bloc. Our findings show greater proximity to the efficiency framework proposed by the AMH, with the emerging markets evidencing an evolutionary behavior, combining a state of generalized efficiency with periods of remarkable inefficiency. Also, the observable synchronization between evolutionary moments and the occurrence of major economic events, both systemic and related to a particular economy, reinforces the need to frame the study of the efficiency of this category of markets within the global economic framework.
Although students theoretically need not consider admission probabilities under strategy-proof mechanisms in school choice problems, our study reveals a significant correlation between students' applications and their beliefs about admission probabilities in the deferred acceptance mechanism. Specifically, students believe they would have a higher probability of matching with the most preferred school if they rank it higher in the application list. Additionally, students tend to lower the rank of the most preferred school if they believe they have too low a probability of matching with it when reporting their true preferences. Students seem to give up the slim chances to be admitted to their most preferred schools and increase the probabilities of matching with the first listed schools in their application lists. Our findings contribute to understanding students' non-truthful behavior in strategy-proof mechanisms.
This paper examines the link between climate risk, energy consumption, and financial market performance in a sample of emerging countries over the period 2000-2024. The objective is to model the dynamic interactions between these three dimensions, in order to understand the extent to which energy dependence and exposure to climate risks influence the stability and resilience of emerging financial markets. We use a panel data covering a representative group of emerging countries to examine the nexus among climate risk, energy consumption, and stock market performance. The estimated models are based on a panel VAR to capture endogenous dynamic effects, on DCC-GARCH model to analyze volatility and conditional correlations, on panel cointegration tests for long-term relationships, and on structural break models to integrate exogenous shocks (2008 financial crisis, COVID-19, war in Ukraine). The results show that climate risk negatively affects stock market performance in emerging countries. The dependence on fossil fuels increases financial vulnerability to climate shocks. Moreover, the increased use of renewable energy mitigates this impact and strengthens the resilience of financial markets. Finally, the intensity of the relationship varies depending on the degree of financial and energy development of emerging countries.
This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior assumptions about their specific identities or functional forms. Our approach then leverages the principle that, under certain conditions, the selection on observables can provide bounds on the selection bias from unobservables. To illustrate the effectiveness of this method, we apply it to an empirical analysis examining the impact of legalized abortion on crime rates.
In the context of global value chains, it is becoming increasingly common for foreign-funded enterprises to participate in local industrial chain activities through shareholding. However, as an external force, do multinational corporations play a balancing role or a collusion role in the production process of enterprises in pollution-intensive host countries? This study explores whether the participation of foreign capitals will drive pollution-intensive local enterprises to realize cleaner production and how it works. We employ a staggered DID model to regress the composition of the nature of equity and the degree of cleaner production of listed firms from China. The result shows that foreign ownership can significantly drive cleaner production by promoting green technology innovation and improving the environmental management capability of domestic polluting enterprises. In addition, the stronger the degree of foreign ownership and the higher the R&D investment, the more obvious the promotional effect of foreign investment on cleaner production of local firms. Moreover, the foreign shareholding serves as a more significant element to realize cleaner production when the percentage of funds from Hong Kong, Macao, and Taiwan of China is higher. This study provides new evidence for the classic “pollution halo” hypothesis from the perspective of foreign equity holdings. In the wave of globalization, it remains important for developing countries to learn advanced environmental management concepts and clean production technologies from foreign capital.
This study investigates the impact of extreme climate events on global systemic financial risk, utilizing a dataset of 32 representative economies from 2004 to 2019. By constructing a Climate Risk Index and a systemic financial risk index (RISK), our findings reveal that extreme climate change significantly exacerbates global systemic financial risk. We find this effect to be particularly pronounced in developing countries. Furthermore, our analysis reveals that country-level ESG performance can effectively mitigate the adverse impact of extreme climate events, with the environmental (E) dimension exhibiting the most prominent moderating effect. We also find that the mitigating efficacy of ESG is conditioned by national cultural values. In addition, this research uncovers a significant synergistic effect between ESG performance and robotics adoption, highlighting a cross-domain strategic complementarity that plays a crucial role in enhancing the resilience of the financial system.
ABSTRACT This study investigates the impact of temporary VAT rate changes on consumer behavior in Vietnam, particularly concerning the VAT reduction implemented during 2023–2024. The research analyzes annual survey data and household expenditure reports to assess changes in consumer spending on durable goods during the first half of 2024 (2024 H1) following the VAT decrease. The results showed that households who were fully aware of the 2% VAT cut were 8 percentage points more likely to plan higher durable‐goods spending in 2024 H1. The spending boost is strongest for low‐wealth and income‐insecure households, confirming that temporary VAT relief mainly stimulates big‐ticket purchases among liquidity‐constrained consumers. The focus on durable goods may limit the applicability of the findings to other product categories. This study focuses on durable goods and may limit the generalizability of findings to other product categories.
Climate change has emerged as a critical barrier to economic development, prompting a global shift toward low-carbon energy systems. For India, whose economy remains heavily reliant on coal, this transition entails complex socioeconomic and institutional challenges related to energy security, livelihoods, and regional dependence. This study assesses India's readiness for a just energy transition by engaging purposively selected respondents from government, research, and civil society sectors. Employing a justice framework that encompasses distributional, recognition, and procedural dimensions, a thematic-analytical approach is used to examine the challenges, opportunities, and impacts shaping India's coal transition. The findings indicate that concerns of distributional justice, particularly the invisibility of informal labor and regional economic dependency, dominate stakeholder perceptions but are closely intertwined with recognition and procedural deficits. Weak procedural inclusion and limited recognition of informal actors reinforce inequities in benefit distribution, highlighting institutional barriers within India's transition architecture. Simultaneously, emerging opportunities through technological innovation, green finance, and inclusive governance hold potential to enhance fairness and resilience, provided they are effectively institutionalized. This study contributes to Global South energy justice debates by offering an analytical understanding of how informality and institutional inertia shape transition outcomes. It underscores that embedding justice principles within governance and policy frameworks through coordination, participatory mechanisms, and targeted inclusion of informal workers is essential for achieving an equitable and sustainable low-carbon future.
How geography affects the choice of institutions is studied in a theoretical model. In this model, nations are located around a circle. Rulers compete through choosing tax rates, the level of military spending, and the degree of formality of institutions. Geographic condition is captured by population density. It is shown that societies with higher population densities choose lower tax rates, establish more formal institutions, and give government officials lower levels of autonomies than those with lower population densities do. A higher level of external threats induces a ruler to choose a higher level of autonomy for officials. The model is illustrated by comparing institutions of agricultural and nomadic regimes in ancient China.
Artificial intelligence (AI) plays an increasingly pivotal role in advancing sustainable economic development. While existing literature predominantly examines the environmental impact of AI technologies from national or sectoral perspectives, this study provides a micro-level analysis of its effects on energy conservation and emission reduction (ECER) performance, utilizing a dataset of Chinese listed firms. We employ a large language model (LLM)-based intelligent scoring system to capture firms' ECER performance from publicly available environmental disclosures, and construct two-pronged measures of AI technological capabilities encompassing both innovation and adoption dimensions. The empirical analysis demonstrates that AI technologies significantly enhance ECER performance among Chinese listed firms, with results remaining robust to various alternative specifications and robustness tests. Mechanism analysis reveals that AI facilitates environmental improvements through the enhancement of productive efficiency and the promotion of green innovation. Heterogeneity analysis further indicates that AI-driven environmental effects are more pronounced among state-owned enterprises, mature-stage firms, firms in polluting industries, sectors with lower competitive intensity, labor-intensive and capital-intensive industries, and firms located in cities with stringent environmental regulations. These findings offer novel firm-level empirical evidence on AI's environmental implications, contributing to a more comprehensive understanding of the technology-environment nexus in emerging economies and laying a theoretical foundation for targeted AI-related environmental policy interventions.
ABSTRACT Land use policies, though seemingly race‐neutral, can inadvertently contribute to racial segregation. Our study focuses on examining the impact of minimum lot size regulations on the likelihood of ethnic minorities integrating into a community, which reveals compelling evidence suggesting that black households exhibit a preference for smaller minimum lot sizes compared to white households. Specifically, our findings indicate that black households are willing to pay $934 to $2126 less annually for every additional acre of minimum lot size, accounting for approximately 3.36%–7.65% of the average house value, after controlling for various other factors influencing housing preferences. The result suggests that minimum lot size regulations can contribute to racial segregation not solely through income disparities but also voluntary choices made by different racial groups. With smaller minimum lot size requirements, communities can foster greater inclusivity and reduce the extent of racial segregation from housing policies.
The paper delves into the role of institutional quality in bolstering China's economic resilience post-COVID-19, CITIC-Entropy. It divides institutions into basic and changeable categories, establishing an index system via the CITIC-Entropy TOPSIS model. Through Markov chain analysis, a consistent uptrend in institutional quality is observed. Notably, a club convergence pattern emerges, indicating gradual progress with limited leaps. The study underscores the pivotal influence of basic economic institutions on disparities in institutional quality, with a diminishing impact from north to south. By refining the evaluation of institutional quality, the research sheds light on its significance in economic resilience while offering guidance for harmonizing market efficiency with governmental efficacy in policy formulation.
To explore the real effect of banking globalisation on bank liquidity creation, we investigate plausibly exogenous variations in the expectation of further banking globalisation under the Belt and Road Initiative (BRI), which further opens the gate to foreign investors. Using data from both listed and unlisted commercial banks in China from 2007 to 2022, we obtain the results showing that implementation of the BRI enhances the on-balance sheet liquidity creation of banks with foreign investors. Further analysis shows that the BRI has more significant positive economic effects on state-owned commercial banks and foreign banks. Additionally, banks with foreign ownership that are small, unlisted, or located in eastern coastal regions create more liquidity since the implementation of the BRI. Our findings indicate that deepening banking globalisation plays an outstanding role in China's banking industry.
The Super-SBM model was utilized to assess and quantify the effectiveness of green development (EGD) in China's eastern and western regions from 2004 to 2020. Building upon this, the kernel density estimation method, the Dagum Gini coefficient method, and the spatial panel convergence model were employed to investigate the dynamic changes, regional disparities, and spatial convergence trends of EGD. This study finds: (1) Both the eastern and western regions experience a specific downward pressure on EGD, demonstrating a spatial pattern characterized by "high in the east and low in the west". (2) The overall difference in EGD between the east and west has an expanding trend, presenting polarization characteristics from regional differences. (3) The EGD between the east and west as a whole has sigma-convergence trend, absolute beta-convergence trend, and conditional beta-convergence trend, and the impact of the industrial composition, the urbanization level, the openness degree, the technological innovation, and the government intervention on EGD has significant regional heterogeneity. The above findings are significant for narrowing the regional differences in EGD and promoting coordinated development of the two regions.
This study investigates the impact of new quality productive forces (NQPFs) on the high-quality development of energy enterprises in China. Using panel data from 572 listed energy enterprises between 2011 and 2022, a comprehensive NQPF index was constructed to evaluate its influence on financial and social performance. The empirical results reveal that NQPF significantly enhances the financial performance and carbon performance of energy enterprises, indicating its role in improving market valuation and reducing carbon emissions. However, the impact of NQPF on overall employment is not significant. Heterogeneity analysis shows that while non-new energy enterprises experience reduced labor demand due to technological substitution, these workers face structural unemployment caused by skill mismatches. Furthermore, NQPF has a stronger impact on financial and carbon performance in non-state-owned enterprises (NSOEs) compared to state-owned enterprises (SOEs). And regional differences are also observed, energy enterprises with eastern regions benefiting more significantly from NQPF than central and western regions. These findings provide valuable insights for governments and enterprise leaders to promote sustainable growth through targeted investments in innovation, green technologies, and workforce development.
We design a controlled laboratory experiment to mitigate moral hazard problems in livestream shopping when sellers make promises to buyers. In our experiment, the promise-keeping reputation mechanism allows sellers to send promises to buyers while buyers can observe the sellers' historical promise-keeping records. Results demonstrate that bare promises under the mechanism significantly enhance trust and trustworthiness. Specifically, bare promises under the promise-keeping reputation mechanism can build trust quickly between buyers and sellers in the beginning; when sellers have a good reputation for promise-keeping, buyers will trust sellers more. When sellers' promise-keeping histories are not recorded, bare promises fail to enhance trust or trustworthiness, as buyers cannot distinguish between trustworthy sellers and opportunistic sellers.
