Bulletin of Economic Research最新文献

Identifying the effects of quantitative easing (QE) on asset return correlations is critical to assessing such policies’ impact across financial markets. In this paper, we use a dynamic conditional correlation model that allows us to measure the impact of unconventional monetary policy on time-varying correlations. Our results suggest that QE significantly affected correlations between stocks and bonds after the Great Recession via short-term portfolio balance effects. The findings are critical for policy-makers and practitioners alike. Central banks should consider the impact of monetary policy on asset correlations in their cost–benefit analyses. Likewise, portfolio managers are encouraged to factor in the effects of monetary policy on correlations to optimize portfolios and reduce potential losses strategically.

This study delves into the intricate dynamics of technology, labor markets, and economic growth within the context of Industry 4.0. By integrating automation capital into a dynamic general equilibrium model, we examine its implications for economic performance and social equity. The empirical analysis highlights the substitutability of unskilled labor by automation, revealing a nuanced relationship between automation adoption, the skill premium, and economic growth. Contrary to conventional wisdom, our findings suggest that a reduced ratio of unskilled to skilled labor, driven by automation, can lead to both an increase in the skill premium and sustained economic growth, even in the face of demographic challenges such as declining populations. However, this trend also exacerbates income inequality, underscoring the imperative for policy interventions aimed at promoting skill enhancement and ensuring equitable distribution of technological advancements.

In the 21st century, various unexpected events such as the financial crisis and COVID-19 have exacerbated the uncertainty of economic policies, whose influence, especially those at the firm level, on the labor share remains to be studied. This article constructs the firm-level economic policy uncertainty (FEPU) through text analysis and empirically analyzes its impact on labor share. Empirical evidence suggests that FEPU can significantly decrease labor share, particularly among firms with financing constraints, low productivity, and high market shares. And the results hold up after a series of robustness tests. Moreover, mechanism analysis indicates that precautionary saving motives play a crucial role in driving firms’ reduction in labor share rather than capital substitution motives. Finally, we further find that although FEPU harms the labor share, it significantly reduces executive payment and has no significant effect on the payment of ordinary employees, thus reducing within-firm inequality. This study enhances our comprehension of how economic policy uncertainty at the firm level affects firm behavior and provides theoretical and practical guidance for increasing labor share and employee welfare.

This paper investigates the changes of gender wage gap in urban and rural areas and examines the effect of wage structure and unobserved characteristics on the gap by using the Chinese Household Income Project (CHIP) survey in 2013 and 2018. We document a significant increase of the gender wage gap in both areas as well as among rural-to-urban migrants. By applying Katz and Murphy's supply-demand framework, we find that the demand has shifted toward younger, more educated workers, and the demand for male workers is higher than that for female workers during the time. The Blinder–Oaxaca decomposition of gender wage gap suggests that factors, such as occupation, parenthood status, and industry, have contributed to the expansion of wage gap. Furthermore, the Juhn–Murphy–Pierce decomposition of the change in gender wage gap implies that the expansion is owing to rising discrimination against females and gender-specific factors such as observed and unobserved characteristics that have performed unfavorably for females.

This paper investigates the optimal choice of firms’ environmental R&D (ER&D) risk in a duopoly market with network externalities and emission tax. Considering consumers’ expectations on the overall network size, we analyze two cases in our model: rational expectations and output commitments. The analysis shows that the ER&D risk increases with the intensity of network externalities and emission tax rate under both rational expectations and output commitments. We also find the ER&D risk is higher under output commitments than under rational expectations. Moreover, whether the private optimum is higher or lower than the social optimum depends on the relationship between the emission tax rate and the marginal environmental damage. Finally, the aforementioned conclusions remain unaffected by alterations in the manner in which competition is carried out, and the ER&D risk is higher under Bertrand competition than under Cournot competition.

Implied subjective probabilities from futures wagering markets are typically determined using a system known as “fair odds.” Here, an alternative system of calculating subjective probabilities—“quasi-parimutuel”—is offered. Instead of considering individual lines independent of the remainder of the wagering opportunities, the quasi-parimutuel method considers the ratios of wagers required between lines such that a constant return is generated for every line. As a result, relative to the fair odds system, favorites (underdogs) have higher (lower) subjective probabilities, and expected returns across all wagers vary.

This paper studies an agent-based model of consumer demand. Agents are heterogeneous with respect to their preferences and incomes. There are two basic ingredients in the model. The first ingredient is a metric that captures the degree of heterogeneity between agents. The second ingredient is a serial computer algorithm that is used in order to compute a terminal consumption bundle at which income is exhausted and overall utility is maximized. Agents are clustered into heterogeneous groups based on their preferences and incomes. We extract information about the evolution of consumer expenditure under different price regimes and the buildup of optimal demand for varying levels of income and preference parameter values. These features cannot be obtained in the classical framework of static utility maximization. Our agent-based data-driven methodology can be applied to any relevant data set and so provide a reliable model for forecasting demand given some agent characteristics.

When managers face relative profit performance competition, we formulate a green managerial delegation contract where the owners impose profit-oriented environmental corporate social responsibility (ECSR) on their managers. We show that the owner adopts ECSR as a commitment device to reduce outputs under quantity competition if the degree of relative profit performance competition is sufficiently high, which can increase not only industry profits but also environmental quality. We also examine an endogenous choice of ECSR and find that the profitable level of ECSR in the asymmetric ECSR case is higher than that in the symmetric ECSR case while both firms undertake ECSR in equilibrium if the severity of competition is sufficiently high.

The COVID-19 pandemic ushered in unprecedented social and economic conditions, alongside unexpected policy responses, challenging the effectiveness of traditional labor market forecasting approaches. This article presents a novel approach that integrates macroeconomic variables, traditional labor market metrics, and Google search data to develop a machine learning-based indicator for the Colombian labor market. We employ support vector machine for regression and neural networks models to forecast monthly employment and unemployment rates, explicitly focusing on the third wave of COVID-19 in the first half of 2021. Our study's findings reveal that the proposed models outperform the autoregressive benchmark regarding forecast accuracy, demonstrating a rapid adaptation to labor market shifts.

This paper investigates the effects of market power on income disparities when firm-specific parameters are considered to test how they shape the gap between capital and labor earnings through their pricing decisions. The dataset consists of 2895 UK manufacturing and services firms over 2010–2019. The results provide the following insights: (a) There is a strong positive association between market power and income disparities across the market, (b) liquidity constraints exert a positive effect on the asset-based disparities ratio, but a negative effect on the profit-based ratio. The robustness of the results is also checked when market-specific characteristics are included in the process.