Economics & Politics最新文献

This study investigates factors influencing the reelection prospects of Brazilian mayors. Analyzing a comprehensive data set spanning 5114 municipalities across four elections reveals that increases in investment and current expenditures before elections pay off at the polls. Moreover, higher average investment expenditures throughout the term enhance reelection chances. The results also indicate that when former term-limited mayors run against the incumbent, reelection probability diminishes, particularly with higher average investment by the previous mayor. Finally, the level of literacy shapes voter attitudes towards opportunistic fiscal strategies: voters with limited literacy are inclined to reward increases in current expenditures, whereas more educated populations prefer increasing investment.

In the United States and other countries, large private firms are increasingly more likely to take public political stances on controversial issues. Firms behave as ideological actors when they take sides in large public debates on social and economic issues. These stances may involve public speech, changes in the terms of service, or in internal reorganization and intrafirm actions. Despite the increase in firms' political actions, firms' ideological orientations remain unexamined. To answer this question, we collect corporate social responsibility statements from Fortune 1000 firms. Using semisupervised topic models, we identify topics that reflect stances on environmental and social issues. We then examine if firms are more likely to take stances on political issues due to pragmatic or ideological factors. We find that while pragmatic considerations play a role, firms' political stances are more driven by the ideological orientation of employees and managers. This research contributes a novel measure of firm ideology and sheds new light on the determinants of corporate political activity.

We investigate the political factors involved in the allocation of public investments into Turkish electoral districts. Using a unique data set covering detailed individual characteristics of approximately 2000 Turkish MPs over five legislative periods during 1987–2004, we show that the composition of several legislator characteristics in an electorate, such as the level of education, area of tertiary degree, and former profession, matters in the way pork barrel occurs across electorates. The findings also indicate a strong presence of partisan motivations and targeted support for opposition groups and ideological strongholds in public investment allocations. We also document evidence that a stronger right-wing tendency in the cabinet, a single-party government, fractionalized voter preferences, and higher voter turnout in the electorate are all associated with increased public investments into specific geographic constituencies.

This paper constructs an institutional investor network based on the heavy holdings of the same stock in China and conducts a social network analysis to investigate the influence of this network on stock price volatility from the perspectives of network structure (density) and location (centrality). The study demonstrates that institutional investor network density is negatively related to stock price volatility, while network centrality is positively related to it. Mechanism analyses further reveal that network density reduces stock price volatility by mitigating private information arbitrage behavior among institutional investors, whereas network centrality increases stock price volatility by creating private information arbitrage opportunities within the network. Additionally, the paper finds that information asymmetry enhances the positive effect of network centrality on stock price volatility. These findings are generally consistent across subsample analyses for different market states, reactions to good and bad news, and types of equity ownership, as well as in other robustness tests. The practical implications of these findings are significant for market stability regulation.

Do women in politics contribute to gender parity in education? This study seeks to provide an empirical answer to this question by examining whether women in politics (women parliamentarians) contribute to closing the gender inequality in education using a global sample of 191 countries from 1990 to 2020. We deployed the two-stage least square (IV-TSLS) technique and gender quota as an instrument to isolate the exogenous effect of women in politics on gender parity in primary, secondary and tertiary education. The findings from the IV-TSLS estimators show that an increase in the number of female parliamentarians is associated with a significant increase in gender parity at all levels of education. These results survived several robustness checks, including using different estimators such as the Lewbel two-stage least squares and the Kinky least-squares estimators. Based on the quota type, we documented that women in politics significantly spur gender parity in education in countries with reserved seat quotas and not in countries with candidate quotas. We also found that the results differ across different geographical regions and income groups. The findings call on policy-makers to address societal, legal and structural barriers limiting women's political participation to achieve gender parity at all levels of education.

This paper examines if politicians react to events they cannot control to avoid political blame and if voters hold politicians accountable for functions beyond their office. I focus on the response of mayors and voters to a farmland tax implemented by the Italian central government. I investigate how the municipalities affected by the new policy adjust to it and study if the election odds of the incumbent mayor's party in towns subject to the tax are affected. Mayors increase spending in municipalities where the tax is implemented. Average spending grows by 1.38 euro (about a 1% increase) and it is financed by increased borrowing which expands by 0.64 euro per capita, on average. Voters do not seem to punish the local incumbent for a policy decided by the national government. Two factors may have contributed to offsetting the electoral impact. The first is greater spending in those municipalities where the incumbent is on the ballot. The second is a media account of the policy which was factual and not biased against the local incumbent. Overall, these findings suggest politicians react to policies that are fully out of their hands, potentially to avoid electoral punishment.

Anticorruption is a prevalent global phenomenon and has yielded many good results. This study empirically tests the real effect of China's anticorruption on corporate acquisition premiums and explores its mechanisms. We find that after the exposure of and crackdown on corrupt provincial officials, firms without political connections had lower mergers and acquisitions (M&A) premiums than those with political connections. Cross-sectional test results show that when firms are private or in areas with high marketization, the anticorruption event has a greater impact on their acquisition premiums. The channel test demonstrates that anticorruption reduces the value of political connections and improves the negotiation advantages of nonpolitically connected firms, enabling them to pay lower M&A premiums. Our findings indicate that anticorruption can create a considerably fair business environment. Moreover, we confirm the real effects of anticorruption on the distortion of resource allocation at the firm level. Finally, the results of this research have policy implications for the world's largest emerging market.

Utilizing text analysis through machine learning techniques, this study investigates the influence of enterprise digital transformation on audit opinions within China's A-share listed companies spanning from 2011 to 2020. The findings underscore that enterprise digital transformation has the potential to bolster standard unqualified audit opinions through the enhancement of internal control quality and information transparency. Additionally, factors such as marketization level, property rights nature, and industry classification are found to be pivotal in shaping this relationship. These research outcomes not only extend the theoretical horizons of audit opinion studies but also offer valuable insights and recommendations for auditors to optimize the efficacy of audit opinions.

Financial frauds can cause serious damage to financial markets but are hard to detect manually. In this study, we develop an intelligent detecting model to efficiently identify financial frauds by using XGBoost on raw financial data items in corporation financial statements. With listed companies in Chinese A-share Market taken as samples, empirical results reveal that the proposed model works better than traditional models by a large margin in detecting fraud. Notably, the proposed model exhibits superior performance when used together with raw financial data items than with financial indicators. Moreover, the proposed model remains robust on outperformance in fraud detection when serial fraud cases are recoded, test periods are altered, more raw financial data are input, as well as other machine learning models–the AdaBoost and SVM–are selected as benchmark models. Our study enriches the application of machine learning in finance sector, and highlights the economic significance of raw financial data as the financial system's most fundamental components.

The advent of the digital economy has ushered in unprecedented opportunities for corporate development. Utilizing a comprehensive data set comprising Chinese listed companies spanning the period 2011–2020, this study empirically examines the impact of digital transformation on corporate illegality. The findings reveal a significant reduction in corporate illegality attributable to digital transformation. This empirical result retains its significance even when subjected to a battery of robustness tests. In terms of the underlying mechanisms, this paper conjecture that digital transformation reduces the internal and external information asymmetry, thereby curbing corporate illegality. Further heterogeneous analysis shows that digital transformation is more effective among corporates with higher agency cost (state-owned or large corporates) or corporates located in regions with lower degree of marketization level. These heterogeneous effects provide supportive evidence to the above conjecture. The implications of this study extend the boundaries of digital transformation research and furnish novel and actionable insights into the prevention of corporate illegality.