Miracle-dz/UniFAR-FTUs huggingface dataset:
Financial versus strategic bidders and underpricing as an acquisition motive

We examine the difference between financial and strategic bidders in exploiting target underpricing. To isolate underpricing from other sources of acquisition gain, we estimate target revaluation of bids that fail to be completed. We document larger revaluations for targets of financial bidders than for those of strategic bidders when targets are most likely to be underpriced, i.e. when they are small. This differential effect between financial and strategic bidders in target revaluation is robust after controlling for differential sorting into deal failure, future takeover activity, and anticipated operational changes, and therefore indicates that, it is greater target underpricing before bid announcements that financial bidders reveal to the market than strategic bidders do. This suggests that, when target underpricing is prevalent, financial bidders seize profit opportunities by bidding on underpriced targets, to a larger extent than strategic bidders.
Biased By Choice: How Financial Constraints Can Reduce Financial Mistakes

We show that constraints can improve financial decision-making by disciplining behavioral biases. In financial markets, restrictions on leverage limit traders’ ability to borrow to open new positions. We demonstrate that regulation that restricts the provision of leverage to retail traders improves trading performance. By increasing the opportunity cost of postponing the realization of losses, leverage constraints improve traders' market timing and reduce their disposition effect. We replicate these findings in two distinct experimental settings, further isolating the mechanism and demonstrating generality of the results. The interaction between constraints and behavioral biases has implications for policy and choice architecture.
Transaction Tax and Market Illiquidity

We identify four interrelated behavioral propositions after the implementation of a seller’s stamp duty (SSD) (a transaction tax on sellers who sell their properties within the SSD lock-in period) in the Singapore private housing market. First, SSD lock-in home sellers may sell their properties at a higher price than ordinary home sellers to cover the SSD tax (the price effect). Second, the SSD lowers the probability that a transaction takes place, prolonging SSD lock-in home sellers’ property holding period (the lock-in effect). The magnitude of this effect is determined by the strength of the SSD tax. Third, the lock-in effect drives some affected home sellers to become SSD lock-in landlords who lease out their properties at a lower rent (the rent effect). SSD lock-in landlords are forced to hold and rent out their properties, and thus, they may have lower search and bargaining power than ordinary landlords do, giving rise to a hidden tax benefit to tenants. Last, the price effect provokes ordinary home sellers to raise their reservation price (the contagion effect). This lowers their probability of finding a home buyer, which amplifies the lock-in effect on market-level illiquidity. Logical coherence and empirical identification of the intertwined behavioral outcomes after implementing an SSD are novel contributions to the literature. The findings have implications for policymakers in designing transaction taxes.
Cross-Border Equity Flows and Information Transmission: Evidence from Chinese Stock Markets

This paper examines the effects of bi-directional cross-border equity flows on stock returns, volatility and valuation differential using the unique Stock Connect program in China as a natural experiment. Via Stock Connect, investors from Hong Kong (mainland China) can trade qualified stocks listed in Shanghai (Hong Kong). We find that southbound (northbound) investors net purchases predict returns of Hong Kong (Shanghai) stocks. However, southbound and northbound trades exhibit asymmetry in volatility-volume relationship; there is a positive (negative) relationship between lagged southbound (northbound) volume and volatility of connected stocks in Hong Kong (Shanghai). Southbound investors net purchase is positively related to lagged AH share price premium for dual-listed stocks and such trades reduces future valuation differential. Our study shows that stock market integration facilitates information sharing and narrow valuation differential across previously segmented markets. But the effects of stock market integration depend importantly on local market environments such as investor clienteles.
Agricultural Networks in Emerging Markets: A Supply Chain Approach

We study the development of effective agricultural supply networks in emerging economies for better utilization of land and downstream processing resources for harvested goods. Using the cotton sector of Mozambique as a prototypical example, we study the decisions made by farmers, down-stream processors and government officials in agribusiness supply chains (agri-chains). The structure/con…guration and management of the supply network, associated sourcing rights of downstream processors, government minimum price guarantees to farmers, and taxes on cross-region ‡flows affect the performance of these chains and are in the domain of our study. We develop a stylized model of an agricultural supply network that consists of two farmers, supported by two downstream processors (ginners), who make two types of fundamental decisions under yield uncertainty: how much land to allocate for planting before the start of the growing season, and, the pricing rules followed by downstream processors that purchase the harvest. We consider a variety of decision making structures, from centralization to complete decentralization, for our agrichains. The resulting analysis depends on the nature of decision-making and on the structure of yield uncertainty. Analytical results supported by numerical experiments, allow us to conclude that appropriately setting minimum price guarantees at intermediate levels, can lead to near …first-best solutions independently of decision rights in agricultural networks. The analysis also suggests that some farmer co-operation in land allocation or regional integration of farmer-ginning assets, together with moderate minimum price guarantees, might be implementable pathways to achieve agri-chain efficiency in emerging economies.
Stocks, Flows, and Flood Insurance: A Nationwide Analysis of the Capitalized Impact of Annual Premium Discounts on Housing Values

The National Flood Insurance Program (NFIP) is chronically insolvent due to the increased intensity and frequency of natural disasters. NFIP was not designed to be actuarially sound; however, the increasing debt associated with NFIP has resulted in policy efforts to increase flood insurance premiums. Despite widespread concerns over the affordability of higher premiums, less attention has been paid to the impact of premium rate increases on housing values and associated homeowner wealth. We use the quasi-experimental nature of eligibility criteria for the largest class of flood insurance premium discounts to causally estimate the capitalization of flood insurance premium subsidies using nationwide and city-specific hedonic difference-in-difference regressions. We find that in a nationally pooled sample, the average capitalization of subsidy eligibility is $11,807 and show that capitalization exhibits significant and intuitive heterogeneity across municipalities. Our results inform ongoing policy discussions surrounding the planned transition to NFIP’s Risk Rating 2.0 premium schedule.
Optimal versus Naive Diversification: False Discoveries, Transaction Costs and Machine Learning

This paper shows that sophisticated diversification strategies never underperform the 1/N rule when adjusting for multiple testing; however, their edge is severely undermined by transaction costs. As a way forward, this paper provides a machine learning approach for ex-ante strategy selection. By linking the characteristics of investment scenarios to the out-of-sample performance of strategies, the algorithm never underperforms the 1/N rule, even in the presence of relatively high transaction costs.
Financial Returns in Major League Soccer

Major League Soccer (MLS) is the top-tier professional soccer league serving the United States and Canada. This study examines factors hypothesized to impact consumer demand for professional sports on team revenue in this nascent league. The estimates are consistent with positive returns to performance, novelty effects from newer teams, and varying impacts from roster quality and composition. Other factors hypothesized to be important for MLS teams (e.g., stadium quality and market demographics) are not associated with team revenue. The estimates are similar to findings in other major North American sports leagues, even though MLS operates with a unique single-entity ownership structure that has the potential to disincentivize individual team investments by league owners.
Stock Returns and Inflation Innovations with State-Dependent Inflation Non-Neutrality

We show that the concurrent relation between quarterly stock returns and inflation innovations is appreciable and robustly significant only over weaker economic times, strikingly positive over 1997:Q4-2017:Q4 but negative over 1981:Q3-1997:Q3. Otherwise, the stock-inflation relation is relatively much smaller and near zero to marginally negative over both our pre-1997 and post-1997 periods. We suggest two complementary channels for understanding our main findings. First, we find consistent state-dependent patterns in how inflation innovations are related to expected economic growth and/or the equity risk premium, suggestive of a ‘state-dependent inflation non-neutrality’ channel. Second, when controlling for more fundamental stock-valuation determinants, the partial stock-inflation relation is diminished modestly but remains important over weaker economic times. Along with other analysis, this suggests a ‘signaling intensity of inflation’ channel where inflation signals are more relevant for identifying the economic state when uncertainty is elevated. JEL Classification: G12
Tax Subsidy Information and Local Economic Effects

We examine whether the relation between business tax subsidies and local economic activity varies based on publicly available subsidy information. State and local business incentives have tripled in size over the past thirty years (Bartik, 2019), now amounting to over 40 percent of total state corporate tax revenues (Slattery and Zidar, 2020). However, the subsidy grant process is notoriously opaque, and transparency problems inhibit clear assessments about whether subsidies achieve their intended outcomes. We find that public information about these incentives – measured based on the existence of state-level subsidy disclosure initiatives, the online publication of subsidy details, and ex ante job commitment disclosures – plays a critical role in subsidy effectiveness. Across all three measures, we observe that the positive association between subsidies and establishments occurs only in those counties with greater information. However, we find that employment effects occur only when the subsidies are accompanied by ex ante job commitments, signaling heterogeneity in the extent to which information facilitates job and wage growth. Our large-scale empirical analysis on the role of public subsidy information provides evidence of an important factor previously discussed, but not empirically tested, in public economics. Furthermore, we offer policy-relevant evidence for the increasing number of states implementing subsidy disclosure regimes.
Demand Estimation and Price Premium of Healthy labeled Foods

The food labeling has become an attractive tool for consumers, suppliers and policymakers. However, the evidence on consumer demand and the effect of food labeling is inconclusive because there are various factors such as presentation of nutritional information, consumer heterogeneity, and food categories. This study describes the substitution and complement patterns among conventional foods and healthy labeled foods, taking consumer heterogeneity and differences in food categories into consideration. We compare three types of healthy labeled foods, nutritional claims, organic and functional foods with government certification. The third healthy labeled food is called as Foods for Specified Health Uses (FOSHU), which is supported by scientific evidence. The demand estimation of healthy foods with scientific evidence is examined. We find that FOSHU can be a complementary good to conventional food, and a substitute for nutritional claims and organic products. These findings suggest the need for public health policymakers to devote attention to price variations of other healthy labeled conventional foods. In addition, we exploit a uniform value-added tax (VAT) hike in Japan in April 2014, and compare the price elasticity before and after the VAT hike. This implies that some food substitution and complement patterns changed after the VAT hike. Therefore, public health policymakers should monitor a tax implementation even if it is not directly relevant to healthy food consumption.
Financial Literacy, Attitudes, and Financial Satisfaction: An Assessment of Credit Card Debt-Taking Behavior of Australians

Unpaid credit card debt can be problematic; people should avoid it where possible. Unlike prior studies, this paper examines the relative strength of the association of financial literacy, attitude towards balancing spending and savings, and financial satisfaction with credit card debt-taking behavior by analyzing the 2016 wave of the Household, Income and Labour Dynamics in Australia (HILDA) Survey. We find that higher financial literacy is associated with less credit card debt. However, incorporating the other factors reduces this relationship. Our results advise policy-makers to include components in the financial literacy curricula which encourage savings attitude to reduce problematic debt-taking.
Derivatized HPTLC Method for Simultaneous Estimation of Glucosamine and Ibuprofen in Tablets

A selective, precise and derivatized HPTLC method has been developed for the simultaneous estimation of Glucosamine and Ibuprofen in tablet formulation. In this method standard and sample solutions of Glucosamine and Ibuprofen were applied on pre-coated silica gel 60F254 TLC plate, and developed using Propanol-Ethyl acetate-Ammonia-Water (4: 3: 2: 1 v/v), as mobile phase and derivatized using Iodine vapor. The drugs on the plate were scanned at 254 nm. The dynamic linearity range was 5-25 μg/spot for Glucosamine and 2-10 μg/spot for Ibuprofen. The method was validated for precision, recovery and reproducibility
Certainly Uncertain: Three Methods of Separating Uncertainty Types

Multiple studies have discovered a role for uncertainty in describing output and employment business cycles. None have separated uncertainty into policy uncertainty and non-policy uncertainty and examined their respective effects. I propose three methods for separating economic uncertainty into disjoint sets: 2 based on textual analysis and a regression method that estimates an unobserved set and is flexible to many applications. The regression method has desirable characteristics in a VAR and Cholesky decomposition context including consistently underestimated IRF coefficients of real variables. Results are robust to alternative dependent and independent variables, VAR specification, unobserved uncertainty sets, time periods, and cotrols. Despite systematic underestimation, non-policy uncertainty shocks have large measured effects on both economic policy uncertainty and output, even when controlling for financial stress. FEVD’s illustrate the explanatory gains from separating uncertainty types. Electronic copy available at: https://ssrn.com/abstract=3271320
Using the JD-R Model to Predict the Organizational Outcomes of Social Workers in Guangzhou, China

Objective: An examination of how job burnout and job satisfaction are jointly associated with social workers’ commitment and turnover intentions is critical to understanding the underlying mechanisms of social workers’ turnover intentions. Using the job demands-resources (JD-R) model, this study examined the relationships between job satisfaction and organizational outcomes (e.g., turnover intentions and organizational commitment) and how job burnout (i.e., exhaustion and cynicism) mediated these relationships. Method: We applied the JD-R model to 748 social workers from the Integrated Family Services Centers in Guangzhou, China. Job demands were measured as workloads, and job resources were measured as support from organizations (e.g., supervisory support) and professional associations (e.g., career development). Results: Our results provide evidence for the extended dual process of the JD-R model: the health-impairment process and the motivation-driven process. Social workers’ job demands (i.e., workload) influenced their intentions to leave the organization, whereas social workers’ job resources predicted their commitment to the organization. Conclusion: Our findings confirm the importance of providing job resources to social workers in Integrated Family Services Centers.
Suicidal Ideation Among International Students: The Role of Cultural, Academic, and Interpersonal Factors

We examined two structural equation models of international students’ suicidal ideation using data from 595 international students in two public universities in the United States. The models represented competing hypotheses about the relationships among discrimination, cross-cultural loss, academic distress, thwarted belongingness, perceived burdensomeness, and suicidal ideation. The findings indicated there were direct, positive links between discrimination, cross-cultural loss, and academic distress to perceived burdensomeness; a direct, positive link between perceived burdensomeness and suicidal ideation; and indirect, positive links between discrimination, cross-cultural loss, and academic distress to suicidal ideation via perceived burdensomeness. The only predictors that related to thwarted belongingness were cross-cultural loss and academic distress, and there were no indirect links to suicidal ideation via thwarted belongingness. In fact, with all other variables in the model, thwarted belongingness was unrelated to suicidal ideation. Finally, academic distress was directly related to suicidal ideation. We discuss implications of the findings.
Agricultural productivity must improve in sub-Saharan Africa

The region must pivot from area expansion to increasing crop yields on existing farmland In the first two decades of the 21st century, sub-Saharan Africa (SSA) has changed rapidly for the better in many ways, counter to many outdated narratives. Many of these improvements—including those in gross domestic product (GDP) per capita, poverty rates, health, life expectancy, education, and agriculture—have been mutually reinforcing (1, 2). SSA achieved the highest rate of growth in agricultural production value (crops and livestock) of any region in the world since 2000, expanding by 4.3% per year in real [inflation-adjusted US dollars (USD)] between 2000 and 2018, roughly double that of the prior three decades. The world average over the same period was 2.7% per year (1). Agricultural value added per worker in real 2010 USD rose from $846 in 2000 to $1563 in 2019, a 3.2% annual rate of growth. But to assert that Africa is rapidly developing does not mean that all livelihood indicators are improving, though most are in most countries (1, 3). SSA faces many major challenges. We focus below on one such challenge, which we see as a precondition for sustaining livelihood improvements in the region: transitioning from area expansion to productivity growth as the source of Africa's agricultural development.
aiai at the FinSBD-3 task: Structure Boundary Detection of Noisy Financial Texts in English and French Using Data Augmentation and Hybrid Deep Learning Model

Both authors contributed equally to this research. This paper presents the method that we tackled the FinSBD-3 shared task (structure boundary detection) to extract the boundaries of sentences, lists, and items, including structure elements like footer, header, tables from noisy unstructured English and French financial texts. The deep attention model based on word embedding using data augmentation and BERT model named as hybrid deep learning model to detect the sentence, list-item, footer, header, tables boundaries in noisy English and French texts and classify the list-item sentences into list & different item types using deep attention model. The experiment is shown that the proposed method could be an effective solution to deal with the FinSBD-3 shared task. The submitted result ranks first based on the task metrics in the final leader board.
A Longitudinal Study of Removed Apps in iOS App Store

To improve app quality and nip the potential threats in the bud, modern app markets have released strict guidelines along with app vetting process before app publishing. However, there has been growing evidence showing the ineffectiveness of app vetting, making potentially harmful and policy-violation apps sneak into the market from time to time. Therefore, app removal is a common practice, and market maintainers have to remove undesired apps from the market periodically in a reactive manner. Although a number of reports and news media have mentioned removed apps, our research community still lacks the comprehensive understanding of the landscape of this kind of apps. To fill the void, in this paper, we present a large-scale and longitudinal study of removed apps in iOS app store. We first make great efforts to record daily snapshot of iOS app store continuously in a span of 1.5 years. By comparing each two consecutive snapshots, we have collected the information of over 1 million removed apps with their accurate removed date. This comprehensive dataset enables us to characterize the overall landscape of removed apps. We observe that, although most of the removed apps are low-quality apps (e.g., outdated and abandoned), a number of the removed apps are quite popular. We further investigate the practical reasons leading to the removal of such popular apps, and observe several interesting reasons, including ranking fraud, fake description, and content issues, etc. More importantly, most of these mis-behaviors can be reflected on app meta information including app description, app review, and ASO keywords. It motivates us to design an automated approach to flagging the removed apps. Experiment result suggests that, even without accessing to the bytecode of mobile apps, we can identify the removed apps with good performance (F1=83%). Furthermore, we are able to flag the removed apps in advance as long as their inappropriate behaviors appear in their metadata. We believe our approach can work as a whistle blower that pinpoints policy-violation behaviors timely, which will be quite effective in improving the app maintenance process.