1,720,998 research outputs found
Not so fast Mr. policy maker ! Novel empirical strategies for evaluating individual corporate tax rate changes and their effects on wages
No full textThis paper contributes to the literature by developing a framework to analyse specific tax-rate changes at the national level. It proposes and compares three new identification strategies: The first specification uses firm reported profitability as the basis for the division of the treatment and control groups. The second sets up a paired cross-country analysis where the tax rate change schedule allows for a comparison between two nations. And the final, builds on Dobbins & Martin (2016) and Atshuler & Liu (2013), identifying the shock through the ownership status of the firm (whether owned by a foreign company or domestic one). All three models use the event-time study design, varying only on certain controls added or removed and on the definition of the treatment and control groups. These identifications contribute to the literature by enabling an analysis for countries that have systematic flat tax structures (i.e. no regional variation built into the statutory tax rate). Ultimately, serving as a tool for a closer scrutiny of tax rate changes as a policy mandate.
The paper looks at the 2014, 2017, and 2013 tax rate changes in Finland, Italy, and Sweden respectively. The study uses firm-level data drawn from Amadeus combined with regional and national level data from Eurostat and the World Bank Database. The paper finds statistically significant results for the three shocks. There are slight discrepancies in the direction of the results across the three models but overall there is enough alignment that the results prove to be promising and certainly warrant further research
Firm Size, R&D Expenditures, and Abnormal Announcement Returns in Technology Mergers and Acquisitions
No full textResearch on M&A in the technology sector suggests that shareholder gains are larger for large acquirers than for small acquirers, due to industry-specific dynamics involving R&D and size. Research on M&A across industries has shown that shareholder gains are significantly higher for small acquirers than for large acquirers. This general trend is known as the “size effect.” I analyze a sample of 1,266 technology-oriented acquisitions of public companies from 1984 to 2019. My results have several implications for the interactions between firm size and R&D in technology M&A and motivate future research focused on this topic
Explaining Acquirer Returns: Does Asset Tangibility and Financial Slack Play a Role?
No full textAcquirer fixed effects alone offer more explanatory power for the variation in takeover returns than an exhaustive list of deal and firm characteristics combined. The interquartile range of 5% between the 25th and 75th percentile acquirer fixed effect is comparable to the interquartile range of acquirer returns. This difference results in significant incremental value creation for shareholders of the acquiring firm. Exploiting serial acquirers and extracting the estimated acquirer fixed effect, this paper explores the economic factors behind this statistical concept. I find that the acquirer’s asset tangibility, or the level of tangible assets held by the firm, is negatively associated with the estimated acquirer fixed effect. This could signal that a higher level of borrowing capacity is vulnerable to similar agency concerns as Jensen’s (1986)“Free Cash Flow Hypothesis.” I use asset tangibility as a proxy for financial slack in the classification structure of Smith and Kim (1994) to analyze acquirer returns. This paper shows that Low-Collateral/High-Investment acquirers perform better on average than High-Collateral/Low-Investment, High-Collateral/High-Investment, and Low-Collateral/Low-Investment acquirers. This contradicts Myers and Majluf's (1984) theory suggesting that maintaining financial slack is beneficial for bidding firms. The modest increase in explanatory power when using the financial slack classifications as fixed effects suggest that certain firms are “better” acquirers irrespective of their financing constraints relative to investment opportunities and irrespective of established explanatory factors
Artificially Intelligent Research Assistance in Economics and Machine Learning
No full textStatistical programming tools like Python, Stata, and R have long been of indispensable value to empirical economists. They have also long been intimidating to students learning economics and, at times, frustrating even to experienced programmers.
In this work I propose a wholly new type of statistical programming. “Athena,” a product I built this year, is a computational tool that knows enough English and enough econometrics to function as a virtual research assistant for its user. The product, which is the first of its kind, uses machine learning and an original context-free grammar (CFG) to understand natural language. This wholly eliminates the need for computer language syntax.
This paper places Athena in the broader academic context of automated semantic parsing and computational research aids, explains Athena’s implementation in both the econometric and natural language parsing (NLP) domains, walks through the product’s functionality with real datasets, and includes a frank discussion of Athena’s pitfalls and limitations
Venture Capital Decision Making Following the Burst of the Dot.com Bubble
No full textThis paper investigates changes in venture capital investing behavior around the dot.com bubble and its subsequent crash in March of 2000. Through various difference in difference models, it estimates the relationship between a fund’s pre-crash tech exposure and its effect on multiple post-crash outcomes. While this paper finds that there was no significant effect between a fund’s pre-crash tech exposure and a portfolio company’s ability to raise capital or exit, it does find that there was a significant effect between a fund’s pre-crash tech exposure and the following, post-crash, 1) a portfolio company raising a later stage round’s ability to raise capital, 2) firms’ ability to raise follow-on rounds of funding, 3) IT firm’s ability to raise follow-on rounds of funding, and 4) how many rounds the VC participated in. Ultimately, it was revealed that, post-crash, Tech VCs began to participate in more rounds, follow-on rounds, and more specifically, their non-IT portfolio companies’ follow-on rounds, proving that Tech VC funds rotated out of tech and into non-IT investments in response to the tech crash
Artificially Intelligent Research Assistance in Economics and Machine Learning
No full textStatistical programming tools like Python, Stata, and R have long been of indispensable value to empirical economists. They have also long been intimidating to students learning economics and, at times, frustrating even to experienced programmers.
In this work I propose a wholly new type of statistical programming. “Athena,” a product I built this year, is a computational tool that knows enough English and enough econometrics to function as a virtual research assistant for its user. The product, which is the first of its kind, uses machine learning and an original context-free grammar (CFG) to understand natural language. This wholly eliminates the need for computer language syntax.
This paper places Athena in the broader academic context of automated semantic parsing and computational research aids, explains Athena’s implementation in both the econometric and natural language parsing (NLP) domains, walks through the product’s functionality with real datasets, and includes a frank discussion of Athena’s pitfalls and limitations
The Impact of Corporate Payout Policy on Shareholder Wealth: Dividends vs. Share Repurchases
No full textMore than Waste: An Empirical Study on the Impact of Renewable Portfolio Standards on the development of Landfill Gas-to-Energy Projects
No full textUniversity Research Efficiency: Breakdown by Type and Funding Source
No full textThe focus of this paper is to research the efficiency of the top universities across the United States. Using data from the 2010s this paper studies the relationship between research output and the sources of funding of universities while also looking at university types. At the university level this paper measures output of patent applications, documents produced, and licensing revenue across eight years and 56 different universities.
With an increase in reliance on university-led research as well as an increase in university and non-federal funding, this paper examines the shift and compares findings to those of Adams Griliches (1998). Running research outputs against R&D spending, this paper finds that universities that have a larger share of non-federal funding have larger output elasticities
Firm Size, R&D Expenditures, and Abnormal Announcement Returns in Technology Mergers and Acquisitions
No full textResearch on M&A in the technology sector suggests that shareholder gains are larger for large acquirers than for small acquirers, due to industry-specific dynamics involving R&D and size. Research on M&A across industries has shown that shareholder gains are significantly higher for small acquirers than for large acquirers. This general trend is known as the “size effect.” I analyze a sample of 1,266 technology-oriented acquisitions of public companies from 1984 to 2019. My results have several implications for the interactions between firm size and R&D in technology M&A and motivate future research focused on this topic
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