European Pharmaceutical Price Regulation, Firm Profitability, and R&D Spending

EU countries closely regulate pharmaceutical prices whereas the U.S. does not. This paper shows how price constraints affect the profitability, stock returns, and R&D spending of EU and U.S. firms. Compared to EU firms, U.S. firms are more profitable, earn higher stock returns, and spend more on research and development (R&D). Some differences have increased over time. In 1986, EU pharmaceutical R&D exceeded U.S. R&D by about 24 percent, but by 2004, EU R&D trailed U.S. R&D by about 15 percent. During these 19 years, U.S. R&D spending grew at a real annual compound rate of 8.8 percent, while EU R&D spending grew at a real 5.4 percent rate. Results show that EU consumers enjoyed much lower pharmaceutical price inflation, however, at a cost of 46 fewer new medicines introduced by EU firms and 1680 fewer EU research jobs.

Financial Risk in the Biotechnology Industry

The biotechnology industry has been an engine of innovation for the U.S. healthcare system and, more generally, the U.S. economy. It is by far the most research intensive industry in the U.S. In our analyses in the current paper, for example, we find that, over the past 25 years, average R&D intensity (R&D spending to total firm assets) for this industry was 38 percent. Consider that over this same period average R&D intensity for all industries was only about 3 percent. In the current paper we examine this industry along a number of dimensions and estimate its average financial risk. Specifically, we use Compustat and Center for Research in Securities Prices (CRSP) data from 1982 to 2005 for firms defined by the North American Industry Classification System (NAICS) as biotechnology firms to estimate several Fama-French three factor return models. The finance literature has established this model as the gold standard. Single factor models like the Capital Asset Pricing Model (CAPM) do not capture all of the types of systematic risk that influence firm cost of capital. In particular, the CAPM does not reflect the empirical evidence that supports both a size-related and a book-to-market related systematic risk factor . Both of these factors, based on biotech industry characteristics, will exert a greater influence on biotech firms, on average. Another implication is, of course, that cost of capital estimates for the industry will be underestimated when a single factor model, like the CAPM, is used. This also implies that the cost estimates of bringing a new drug and/or biologic to market will be understated if financial risk and cost of capital are measured using a single-factor model. In the current study we find that biotechnology firms are exposed to greater financial risk than other industries and are also more sensitive to policy shocks that affect, or could affect, industry profitability. Average nominal costs of capital over the 1982-2005 time period were 16.25 percent for biotechnology firms. Of course, these average estimates obscure significant variation in financial risk at the firm level, but nonetheless shed light on some interesting aggregate differences in risk. In the current paper we discuss the theoretical links between financial risk, stock prices and returns, and R&D spending. Several caveats are also discussed.

FDA New Drug Approval Times, Prescription Drug User Fees, and R & D Spending

FDA-approval times have declined significantly since the enactment of the Prescription Drug User Fee Act (PDUFA) in 1992. As a result, present value expected returns to pharmaceutical R&D have likely increased. In the current paper we employ a unique survey dataset, which includes for the first time data on firm-level pharmaceutical R&D. We estimate the effects that FDA-approval times have on R&D investments. Controlling for other factors such as pharmaceutical profitability and cash flows, we find that a 10 percent decrease (increase) in FDA-approval times results in a 1.7 percent in increase (decrease) in R&D spending.Combining this estimate with previous research and publicly available data on industry-level pharmaceutical spending between 1992 and 2001, we conclude PDUFA, and its subsequent renewals, stimulated an additional 13.5 billion in pharmaceutical R&D (2005 U.S.), and has presumably continued to do so since 2001. Recent economic research has shown the social rate of return on pharmaceutical R&D is remarkably high; thus, the social benefits of PDUFA (over and above the benefits of more rapid consumer access) are likely to be substantial.

Do investors see through mistakes in reported earnings?

This study investigates whether investors see through materially misstated earnings, and whether they anticipate earnings restatements. For firms that restate at least one annual report, we find that investors are misled by mistakes in reported earnings at the time of initial earnings announcements. Investors react positively to the component of the favorable earnings surprise that will subsequently be restated, and attach the same valuation to it as to the true earnings surprise. We also find that investors anticipate the subsequent downward restatements and start marking stock prices down several months before a restatement announcement, so that the full impact of a restatement is about three times as large as the initial announcement effect. Overall our findings indicate that although investors anticipate restatements several months before its announcement, they are misled by misstated earnings for several years and therefore would benefit from better quality of financial information

Two real parton contributions to non-singlet kernels for exclusive QCD DGLAP evolution

Results for the two real parton differential distributions needed for implementing a next-to-leading order (NLO) parton shower Monte Carlo are presented. They are also integrated over the phase space in order to provide solid numerical control of the MC codes and for the discussion of the differences between the standard $\bar{MS}$ factorization and Monte Carlo implementation at the level of inclusive NLO evolution kernels. Presented results cover the class of non-singlet diagrams entering into NLO kernels. The classic work of Curci-Furmanski-Pertonzio was used as a guide in the calculations.Comment: 34 pages, 3 figure

The Effects of Incentive Compensation Contracts on the Risk and Return Performance of Commodity Trading Advisors

This paper shows that commodity trading advisors' (CTAs) investment performance may be partially explained by their incentive compensation contracts. Contracts include base, incentive and asset parameters. The relationships between contract parameters and performance are theoretically indeterminate but are examined here empirically. Results indicate that incentive parameters are positively related to return means and standard deviations. The dollar amounts of assets CTAs manage are negatively related to return means and standard deviations, supporting Elton et al.'s (1987, 1989) finding that CTA performance falls after public offerings of commodity funds. Intuitively, since dollar fees are a function of assets, at the higher asset and fee levels achieved through commodity fund offerings, CTAs may safeguard assets and fees by pursuing less risky investment strategies.incentive compensation contracts, commodity trading advisors, agency theory, commodity fund performance, options