Economic Modelling最新文献

The impact of financial openness on banking stability is complex, with debate on its benefits and drawbacks. Theoretical literature suggests a positive relationship between financial openness and growth, development, and stability, but empirical studies reveal conflicting evidence. This paper examines these contradictions by analyzing data from 58 countries between 2010 and 2020. Using various measures for financial openness and stability, and a double debiased machine learning (DDML) model to control for confounders, we find that financial openness generally enhances banking stability, evidenced by lower nonperforming loan ratios, higher capital adequacy ratios, and increased bank liquidity. However, receptiveness to capital inflows heightens financial vulnerability. Policy implications suggest deeper integration with global markets promotes stability without harming bank profitability, advising against prolonged use of macroprudential policies which hinder development. Our results emphasize careful proxy selection for financial openness and stability, advocating sophisticated techniques like DDML to uncover direct effects.

Digitalization has brought a substantial economic impact on firms' production and operation. This study utilizes firm-level data from the China National Tax Statistics Database to investigate the impact of the Broadband China Strategy on firms’ inventory levels, which are an important strategic resource for firms. We find that Internet access and development result in a sharp decrease in inventory levels, particularly in small and medium-sized enterprises. Furthermore, digital infrastructure can mitigate the negative effects of an insufficient supply of transportation infrastructure. This paper also shows that the enhancements in inventory management are attributable to the increased adoption and improved affordability of broadband Internet among firms. We discuss the role of inventory, providing a thorough understanding of the logic behind the enhanced productivity improvements brought about by digitalization.

This paper discusses the European option pricing problem in the context of asset prices being influenced by liquidity risks and economic cycles. We employ regime switching for asset volatility, and liquidity risks are captured by market-wide liquidity. We obtain an analytical formulation of European option prices, allowing for fast model calibration using real-market data. By estimating model parameters using real option data, we show that pricing errors can be significantly reduced using our model that considers stochastic liquidity, indicating that our model has real-world applications. Our results can help investors and regulators better understand the market and provide a potentially effective risk management tool.

This study examines the impact of labour force participation (LFP) on search behaviour and unemployment in response to uncertainty shocks. Using a Bayesian vector autoregression model, this study shows that an increase in uncertainty raises unemployment, lowers inflation and decreases LFP and search intensity. Then, a New Keynesian model that incorporates endogenous LFP and variable search intensity is constructed. Results show that both search intensity and participation are procyclical, which suggests a discouragement effect. However, with habit formation, the wealth effect outweighs the discouragement effect and induces an increase in LFP, resulting in a more significant decline in aggregate search intensity due to the expanded searcher pool. In the exogenous LFP model, search intensity is countercyclical, which dampens the unemployment rate. In the endogenous LFP model, the increased entry of non-participants cancels out the countercyclical search intensity of unemployed workers due to the large number of searchers.

Recently, supply chain finance (SCF) digitalization, which integrates emerging digital technologies with traditional SCF, has been attracting worldwide attention. While previous studies have highlighted the adoption of SCF digitalization, little is known about how it shapes corporate behaviors. Using a sample of Chinese A-listed firms from 2008 to 2021, this study investigates the relationship between SCF digitalization and corporate financial fraud. Based on the results of the propensity score matching and difference-in-differences approach and mechanism analysis, SCF digitalization is found to inhibit corporate financial fraud by reducing a firm's relational transactions with its suppliers and customers. Additionally, cross-sectional analysis reveals that the governance effect is more pronounced for small- and medium-sized enterprises and for companies with higher information asymmetry, more financial linkages, and lower financial flexibility. Overall, our findings facilitate the understanding of how the digital economy influences corporate behaviors.

This paper studies the effect of household debt on consumption throughout the business cycle. We use household-level data for Spain in a period, 2002–2017, characterized by significant fluctuations in leverage, consumption, and asset prices. We find that high levels of debt have a negative effect on consumption during recession periods, while previous debt accumulation does not significantly influence consumption. When considering heterogeneities across types of debt, we observe that households adjust their spending faster in response to debt not associated with real estate assets. By exploiting explicit information on household credit constraints, we find no evidence suggesting that they play a significant role in shaping the debt-consumption nexus. We conclude that in a situation of high leverage and financial stress, debt overhang decreases household consumption. In this context, policies aimed at preventing households from leveraging excessively during expansions, and policies providing debt relief during recessions, can help mitigate consumption shocks.

Environmental regulations, particularly tax-based measures, significantly impact firm productivity and corporate behavior. This study uses China's Environmental Protection Tax (EPT) law as a quasi-natural experiment to explore whether and how such tax-based environmental regulations influence the productivity of heavily polluting firms. Using a difference-in-differences approach, we find that the EPT law has positively impacted firm productivity by fostering higher research and development investments and encouraging the substitution of labor with capital. The productivity-enhancing effect is more pronounced for state-owned enterprises, large firms, firms with fewer financial constraints, firms receiving more government subsidies, and firms operating in less competitive sectors. These findings support the Porter hypothesis, suggesting that well-designed environmental regulations can stimulate innovation and improve competitiveness, ultimately enhancing productivity. This study underscores the importance of tax-based environmental regulations in promoting productivity and economic growth, providing valuable insights for policymakers aiming to balance environmental protection with economic development.

Digital technology has altered the geographic distribution of knowledge in regional innovation. Existing studies emphasize the role of firms in the digitalization and innovation nexus, whereas there is little evidence on the effect of consumers' digital engagement on innovation capacity. Using data of 211 cities from 2015 to 2018 in China, this study investigates whether and how consumers' digital engagement affects regional innovation capacity. Our empirical results show that cities with greater knowledge diffusion embedded in consumer digital engagement benefit more from increased regional innovation capacity. Further analyses show that cities with higher digital consumer participation have higher innovation output, more entrepreneurial activities, and increased financial access, boosting city-level knowledge generation and commercialization. Our findings also reveal that consumers’ digital engagement is more beneficial in relatively developing regions, including western, peripheral, and less innovative cities, thereby alleviating the concentration of innovation to some extent.

This study implements a novel method to assess subnational welfare differences, addressing the limitations of traditional measures based solely on output or consumption, and ordinal measures such as HDI. We develop a unified and theoretically grounded welfare measure that incorporates consumption, leisure, inequality in consumption and leisure, and life expectancy. The resulting welfare measure is cardinal and interpretable as a consumption equivalent, offering an advantage over ordinal indices such as HDI. Applying this method to Nigeria, the analysis reveals that welfare is positively correlated with consumption and HDI because all incorporate aspects of consumption, inequality, and health. However, welfare differences are four times greater than those suggested by consumption alone, with significantly different rankings, underscoring the critical roles of health and inequality in welfare. Additionally, the innovative inclusion of leisure, measured as non-labor time, significantly changes welfare rankings compared to HDI or IHDI.

We perform several trend-cycle decompositions through the lens of two unobserved components models, herein estimated for Portugal and the euro area. Our procedure copes with the COVID-19’s consequences by explicitly considering potentially larger second moments during that period. This is achieved through a set of pandemic-specific shocks affecting only the 2020–21 period and embedded into estimation through a piecewise linear Kalman filter. Our methodology generates negligible historical revisions in key smoothed variables when the sample period is expanded until 2021:4, since pandemic shocks absorb a great deal of data volatility with minimal impacts on filtered data revisions or estimated parameters. Furthermore, non-pandemic shock volatility remains largely unaffected by the pandemic period. Innovations affecting the cycle in our preferred model are the key propellers of GDP developments during the COVID-19 pandemic period.